/scratch/zt1/project/sshah389-prj/user/snallani/myenv/lib/python3.10/site-packages/hdmf/spec/namespace.py:535: UserWarning: Ignoring cached namespace 'hdmf-common' version 1.5.0 because version 1.8.0 is already loaded.
  warn("Ignoring cached namespace '%s' version %s because version %s is already loaded."
/scratch/zt1/project/sshah389-prj/user/snallani/myenv/lib/python3.10/site-packages/hdmf/spec/namespace.py:535: UserWarning: Ignoring cached namespace 'core' version 2.4.0 because version 2.8.0 is already loaded.
  warn("Ignoring cached namespace '%s' version %s because version %s is already loaded."
/scratch/zt1/project/sshah389-prj/user/snallani/myenv/lib/python3.10/site-packages/hdmf/spec/namespace.py:535: UserWarning: Ignoring cached namespace 'hdmf-experimental' version 0.1.0 because version 0.5.0 is already loaded.
  warn("Ignoring cached namespace '%s' version %s because version %s is already loaded."
Loading data with bin_width=100ms, stride=10ms, spike_processing='count'
Processing MC_MAZE data from scratch...
Applying spike processing: 'count'
BEFORE processing - spike_rates sample (first 3 timesteps, first 10 neurons):
[[2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
Applied COUNT processing: keeping raw spike counts
AFTER processing - spike_rates sample (first 3 timesteps, first 10 neurons):
[[2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
spike_processing mode: count
Data type: float32, Min: 0.00, Max: 15.00
Spike COUNTS (for SNN) sample 5x10:
 [[2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [1. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [1. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
Spike RATES (for KF/LSTM) sample 5x10:
 [[20.  0.  0.  0.  0.  0.  0.  0.  0.  0.]
 [20.  0.  0.  0.  0.  0.  0.  0.  0.  0.]
 [20.  0.  0.  0.  0.  0.  0.  0.  0.  0.]
 [10.  0.  0.  0.  0.  0.  0.  0.  0.  0.]
 [10.  0.  0.  0.  0.  0.  0.  0.  0.  0.]]
Spike rates shape: (94095, 182)
Hand velocity shape: (94095, 2)
Raw data loaded and windowed.
Total unique trials: 2295
Splitting each random permutation into: 1606 train, 344 validation, 345 test trials

--- Split 1/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [43.34461   6.775136], Vel Std (local): [340.67813 289.79938]

Split 1 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 1...
Using device: cuda
Epoch [1/50], Train Loss: 0.9580, Val Loss: 0.9016, Val Corr X: 0.4715, Val Corr Y: 0.4705
Epoch [2/50], Train Loss: 0.7727, Val Loss: 0.6433, Val Corr X: 0.6738, Val Corr Y: 0.5656
Epoch [3/50], Train Loss: 0.6026, Val Loss: 0.5405, Val Corr X: 0.7427, Val Corr Y: 0.6504
Epoch [4/50], Train Loss: 0.5069, Val Loss: 0.4809, Val Corr X: 0.7816, Val Corr Y: 0.6807
Epoch [5/50], Train Loss: 0.4472, Val Loss: 0.4473, Val Corr X: 0.7970, Val Corr Y: 0.7123
Epoch [6/50], Train Loss: 0.4192, Val Loss: 0.4059, Val Corr X: 0.8122, Val Corr Y: 0.7340
Epoch [7/50], Train Loss: 0.3783, Val Loss: 0.3841, Val Corr X: 0.8232, Val Corr Y: 0.7565
Epoch [8/50], Train Loss: 0.3506, Val Loss: 0.3703, Val Corr X: 0.8316, Val Corr Y: 0.7668
Epoch [9/50], Train Loss: 0.3390, Val Loss: 0.3450, Val Corr X: 0.8455, Val Corr Y: 0.7761
Epoch [10/50], Train Loss: 0.3173, Val Loss: 0.3316, Val Corr X: 0.8519, Val Corr Y: 0.7879
Epoch [11/50], Train Loss: 0.3007, Val Loss: 0.3231, Val Corr X: 0.8572, Val Corr Y: 0.7967
Epoch [12/50], Train Loss: 0.2904, Val Loss: 0.3094, Val Corr X: 0.8629, Val Corr Y: 0.8035
Epoch [13/50], Train Loss: 0.2764, Val Loss: 0.3024, Val Corr X: 0.8659, Val Corr Y: 0.8105
Epoch [14/50], Train Loss: 0.2644, Val Loss: 0.2949, Val Corr X: 0.8706, Val Corr Y: 0.8139
Epoch [15/50], Train Loss: 0.2564, Val Loss: 0.2861, Val Corr X: 0.8747, Val Corr Y: 0.8201
Epoch [16/50], Train Loss: 0.2576, Val Loss: 0.3109, Val Corr X: 0.8761, Val Corr Y: 0.8145
Epoch [17/50], Train Loss: 0.2635, Val Loss: 0.2964, Val Corr X: 0.8774, Val Corr Y: 0.8209
Epoch [18/50], Train Loss: 0.2466, Val Loss: 0.2894, Val Corr X: 0.8798, Val Corr Y: 0.8288
Epoch [19/50], Train Loss: 0.2326, Val Loss: 0.2732, Val Corr X: 0.8814, Val Corr Y: 0.8320
Epoch [20/50], Train Loss: 0.2287, Val Loss: 0.2697, Val Corr X: 0.8849, Val Corr Y: 0.8331
Epoch [21/50], Train Loss: 0.2218, Val Loss: 0.2619, Val Corr X: 0.8870, Val Corr Y: 0.8350
Epoch [22/50], Train Loss: 0.2146, Val Loss: 0.2630, Val Corr X: 0.8876, Val Corr Y: 0.8374
Epoch [23/50], Train Loss: 0.2162, Val Loss: 0.2528, Val Corr X: 0.8917, Val Corr Y: 0.8389
Epoch [24/50], Train Loss: 0.2077, Val Loss: 0.2535, Val Corr X: 0.8915, Val Corr Y: 0.8417
Epoch [25/50], Train Loss: 0.2007, Val Loss: 0.2600, Val Corr X: 0.8928, Val Corr Y: 0.8410
Epoch [26/50], Train Loss: 0.2088, Val Loss: 0.2434, Val Corr X: 0.8949, Val Corr Y: 0.8457
Epoch [27/50], Train Loss: 0.1987, Val Loss: 0.2442, Val Corr X: 0.8949, Val Corr Y: 0.8456
Epoch [28/50], Train Loss: 0.1923, Val Loss: 0.2501, Val Corr X: 0.8962, Val Corr Y: 0.8454
Epoch [29/50], Train Loss: 0.1892, Val Loss: 0.2490, Val Corr X: 0.8974, Val Corr Y: 0.8451
Epoch [30/50], Train Loss: 0.1853, Val Loss: 0.2357, Val Corr X: 0.8981, Val Corr Y: 0.8525
Epoch [31/50], Train Loss: 0.1807, Val Loss: 0.2383, Val Corr X: 0.8994, Val Corr Y: 0.8522
Epoch [32/50], Train Loss: 0.1821, Val Loss: 0.2337, Val Corr X: 0.8995, Val Corr Y: 0.8530
Epoch [33/50], Train Loss: 0.1750, Val Loss: 0.2557, Val Corr X: 0.8986, Val Corr Y: 0.8478
Epoch [34/50], Train Loss: 0.2081, Val Loss: 0.2411, Val Corr X: 0.9003, Val Corr Y: 0.8522
Epoch [35/50], Train Loss: 0.1900, Val Loss: 0.2457, Val Corr X: 0.9015, Val Corr Y: 0.8507
Epoch [36/50], Train Loss: 0.1866, Val Loss: 0.2791, Val Corr X: 0.8968, Val Corr Y: 0.8434
Epoch [37/50], Train Loss: 0.1915, Val Loss: 0.2361, Val Corr X: 0.9001, Val Corr Y: 0.8548
Epoch [38/50], Train Loss: 0.1807, Val Loss: 0.2362, Val Corr X: 0.8996, Val Corr Y: 0.8534
Epoch [39/50], Train Loss: 0.1669, Val Loss: 0.2341, Val Corr X: 0.9018, Val Corr Y: 0.8576
Epoch [40/50], Train Loss: 0.1651, Val Loss: 0.2304, Val Corr X: 0.9039, Val Corr Y: 0.8544
Epoch [41/50], Train Loss: 0.1629, Val Loss: 0.2312, Val Corr X: 0.9046, Val Corr Y: 0.8563
Epoch [42/50], Train Loss: 0.1638, Val Loss: 0.2301, Val Corr X: 0.9039, Val Corr Y: 0.8583
Epoch [43/50], Train Loss: 0.1598, Val Loss: 0.2215, Val Corr X: 0.9070, Val Corr Y: 0.8592
Epoch [44/50], Train Loss: 0.1592, Val Loss: 0.2332, Val Corr X: 0.9061, Val Corr Y: 0.8571
Epoch [45/50], Train Loss: 0.1660, Val Loss: 0.2308, Val Corr X: 0.9070, Val Corr Y: 0.8560
Epoch [46/50], Train Loss: 0.1542, Val Loss: 0.2204, Val Corr X: 0.9082, Val Corr Y: 0.8611
Epoch [47/50], Train Loss: 0.1553, Val Loss: 0.2368, Val Corr X: 0.9066, Val Corr Y: 0.8556
Epoch [48/50], Train Loss: 0.1640, Val Loss: 0.2266, Val Corr X: 0.9083, Val Corr Y: 0.8621
Epoch [49/50], Train Loss: 0.1476, Val Loss: 0.2188, Val Corr X: 0.9101, Val Corr Y: 0.8639
Epoch [50/50], Train Loss: 0.1510, Val Loss: 0.2178, Val Corr X: 0.9109, Val Corr Y: 0.8610
Model saved at snn_mcmaze_split_1.pth. Exiting training loop.

--- Evaluating on Test Set for Split 1 ---
Loading model from snn_mcmaze_split_1.pth for testing...

Test Set Results (Split 1):
  Loss: 0.2225
  Correlation X: 0.9128
  Correlation Y: 0.8587
--------------------------

--- Split 2/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [55.528496  4.914141], Vel Std (local): [339.84723 290.3257 ]

Split 2 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 2...
Using device: cuda
Epoch [1/50], Train Loss: 0.8632, Val Loss: 0.6553, Val Corr X: 0.6912, Val Corr Y: 0.5547
Epoch [2/50], Train Loss: 0.6966, Val Loss: 0.6544, Val Corr X: 0.7174, Val Corr Y: 0.6148
Epoch [3/50], Train Loss: 0.5864, Val Loss: 0.5891, Val Corr X: 0.7487, Val Corr Y: 0.6455
Epoch [4/50], Train Loss: 0.5393, Val Loss: 0.4828, Val Corr X: 0.7737, Val Corr Y: 0.6777
Epoch [5/50], Train Loss: 0.4680, Val Loss: 0.4486, Val Corr X: 0.7998, Val Corr Y: 0.7083
Epoch [6/50], Train Loss: 0.4254, Val Loss: 0.4175, Val Corr X: 0.8145, Val Corr Y: 0.7187
Epoch [7/50], Train Loss: 0.3891, Val Loss: 0.4011, Val Corr X: 0.8226, Val Corr Y: 0.7443
Epoch [8/50], Train Loss: 0.3718, Val Loss: 0.3767, Val Corr X: 0.8319, Val Corr Y: 0.7553
Epoch [9/50], Train Loss: 0.3452, Val Loss: 0.3670, Val Corr X: 0.8383, Val Corr Y: 0.7697
Epoch [10/50], Train Loss: 0.3296, Val Loss: 0.3490, Val Corr X: 0.8452, Val Corr Y: 0.7745
Epoch [11/50], Train Loss: 0.3108, Val Loss: 0.3389, Val Corr X: 0.8502, Val Corr Y: 0.7836
Epoch [12/50], Train Loss: 0.2921, Val Loss: 0.3276, Val Corr X: 0.8549, Val Corr Y: 0.7943
Epoch [13/50], Train Loss: 0.2905, Val Loss: 0.3131, Val Corr X: 0.8608, Val Corr Y: 0.8026
Epoch [14/50], Train Loss: 0.2690, Val Loss: 0.3057, Val Corr X: 0.8655, Val Corr Y: 0.8071
Epoch [15/50], Train Loss: 0.2626, Val Loss: 0.3049, Val Corr X: 0.8690, Val Corr Y: 0.8118
Epoch [16/50], Train Loss: 0.2545, Val Loss: 0.2887, Val Corr X: 0.8732, Val Corr Y: 0.8193
Epoch [17/50], Train Loss: 0.2411, Val Loss: 0.2834, Val Corr X: 0.8772, Val Corr Y: 0.8215
Epoch [18/50], Train Loss: 0.2398, Val Loss: 0.3152, Val Corr X: 0.8794, Val Corr Y: 0.8156
Epoch [19/50], Train Loss: 0.2514, Val Loss: 0.2907, Val Corr X: 0.8827, Val Corr Y: 0.8238
Epoch [20/50], Train Loss: 0.2350, Val Loss: 0.2767, Val Corr X: 0.8850, Val Corr Y: 0.8286
Epoch [21/50], Train Loss: 0.2256, Val Loss: 0.2752, Val Corr X: 0.8849, Val Corr Y: 0.8347
Epoch [22/50], Train Loss: 0.2132, Val Loss: 0.2653, Val Corr X: 0.8885, Val Corr Y: 0.8359
Epoch [23/50], Train Loss: 0.2175, Val Loss: 0.2599, Val Corr X: 0.8906, Val Corr Y: 0.8386
Epoch [24/50], Train Loss: 0.2090, Val Loss: 0.2540, Val Corr X: 0.8905, Val Corr Y: 0.8410
Epoch [25/50], Train Loss: 0.2024, Val Loss: 0.2571, Val Corr X: 0.8912, Val Corr Y: 0.8432
Epoch [26/50], Train Loss: 0.1993, Val Loss: 0.2666, Val Corr X: 0.8927, Val Corr Y: 0.8391
Epoch [27/50], Train Loss: 0.2231, Val Loss: 0.2588, Val Corr X: 0.8924, Val Corr Y: 0.8422
Epoch [28/50], Train Loss: 0.2092, Val Loss: 0.2483, Val Corr X: 0.8938, Val Corr Y: 0.8461
Epoch [29/50], Train Loss: 0.2013, Val Loss: 0.2504, Val Corr X: 0.8950, Val Corr Y: 0.8461
Epoch [30/50], Train Loss: 0.1962, Val Loss: 0.2500, Val Corr X: 0.8940, Val Corr Y: 0.8482
Epoch [31/50], Train Loss: 0.1892, Val Loss: 0.2460, Val Corr X: 0.8973, Val Corr Y: 0.8491
Epoch [32/50], Train Loss: 0.1870, Val Loss: 0.2361, Val Corr X: 0.8986, Val Corr Y: 0.8517
Epoch [33/50], Train Loss: 0.1755, Val Loss: 0.2349, Val Corr X: 0.8997, Val Corr Y: 0.8523
Epoch [34/50], Train Loss: 0.1758, Val Loss: 0.2377, Val Corr X: 0.9006, Val Corr Y: 0.8528
Epoch [35/50], Train Loss: 0.1853, Val Loss: 0.2335, Val Corr X: 0.9001, Val Corr Y: 0.8543
Epoch [36/50], Train Loss: 0.1849, Val Loss: 0.2370, Val Corr X: 0.9002, Val Corr Y: 0.8558
Epoch [37/50], Train Loss: 0.1782, Val Loss: 0.2412, Val Corr X: 0.8997, Val Corr Y: 0.8541
Epoch [38/50], Train Loss: 0.1719, Val Loss: 0.2317, Val Corr X: 0.9015, Val Corr Y: 0.8573
Epoch [39/50], Train Loss: 0.1679, Val Loss: 0.2340, Val Corr X: 0.9026, Val Corr Y: 0.8562
Epoch [40/50], Train Loss: 0.1646, Val Loss: 0.2358, Val Corr X: 0.9035, Val Corr Y: 0.8545
Epoch [41/50], Train Loss: 0.1758, Val Loss: 0.2293, Val Corr X: 0.9046, Val Corr Y: 0.8566
Epoch [42/50], Train Loss: 0.1657, Val Loss: 0.2279, Val Corr X: 0.9046, Val Corr Y: 0.8589
Epoch [43/50], Train Loss: 0.1626, Val Loss: 0.2304, Val Corr X: 0.9053, Val Corr Y: 0.8579
Epoch [44/50], Train Loss: 0.1675, Val Loss: 0.2288, Val Corr X: 0.9056, Val Corr Y: 0.8573
Epoch [45/50], Train Loss: 0.1636, Val Loss: 0.2233, Val Corr X: 0.9064, Val Corr Y: 0.8596
Epoch [46/50], Train Loss: 0.1575, Val Loss: 0.2245, Val Corr X: 0.9076, Val Corr Y: 0.8579
Epoch [47/50], Train Loss: 0.1531, Val Loss: 0.2224, Val Corr X: 0.9074, Val Corr Y: 0.8597
Epoch [48/50], Train Loss: 0.1548, Val Loss: 0.2183, Val Corr X: 0.9088, Val Corr Y: 0.8612
Epoch [49/50], Train Loss: 0.1585, Val Loss: 0.3310, Val Corr X: 0.9069, Val Corr Y: 0.8270
Epoch [50/50], Train Loss: 0.2501, Val Loss: 0.2897, Val Corr X: 0.9061, Val Corr Y: 0.8342
Model saved at snn_mcmaze_split_2.pth. Exiting training loop.

--- Evaluating on Test Set for Split 2 ---
Loading model from snn_mcmaze_split_2.pth for testing...

Test Set Results (Split 2):
  Loss: 0.2903
  Correlation X: 0.9132
  Correlation Y: 0.8247
--------------------------

--- Split 3/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [49.88054    4.3394322], Vel Std (local): [339.2272  290.46942]

Split 3 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 3...
Using device: cuda
Epoch [1/50], Train Loss: 0.9572, Val Loss: 0.9144, Val Corr X: 0.4739, Val Corr Y: 0.4937
Epoch [2/50], Train Loss: 0.7603, Val Loss: 0.6900, Val Corr X: 0.7141, Val Corr Y: 0.5710
Epoch [3/50], Train Loss: 0.6123, Val Loss: 0.5444, Val Corr X: 0.7579, Val Corr Y: 0.6359
Epoch [4/50], Train Loss: 0.5014, Val Loss: 0.4967, Val Corr X: 0.7963, Val Corr Y: 0.6656
Epoch [5/50], Train Loss: 0.4453, Val Loss: 0.4896, Val Corr X: 0.8107, Val Corr Y: 0.6867
Epoch [6/50], Train Loss: 0.4212, Val Loss: 0.4364, Val Corr X: 0.8301, Val Corr Y: 0.7141
Epoch [7/50], Train Loss: 0.3921, Val Loss: 0.3977, Val Corr X: 0.8408, Val Corr Y: 0.7357
Epoch [8/50], Train Loss: 0.3576, Val Loss: 0.3790, Val Corr X: 0.8516, Val Corr Y: 0.7414
Epoch [9/50], Train Loss: 0.3369, Val Loss: 0.3603, Val Corr X: 0.8584, Val Corr Y: 0.7570
Epoch [10/50], Train Loss: 0.3191, Val Loss: 0.3578, Val Corr X: 0.8611, Val Corr Y: 0.7696
Epoch [11/50], Train Loss: 0.3128, Val Loss: 0.3394, Val Corr X: 0.8686, Val Corr Y: 0.7739
Epoch [12/50], Train Loss: 0.2942, Val Loss: 0.3218, Val Corr X: 0.8741, Val Corr Y: 0.7871
Epoch [13/50], Train Loss: 0.2798, Val Loss: 0.3190, Val Corr X: 0.8760, Val Corr Y: 0.7925
Epoch [14/50], Train Loss: 0.2726, Val Loss: 0.3060, Val Corr X: 0.8828, Val Corr Y: 0.7973
Epoch [15/50], Train Loss: 0.2647, Val Loss: 0.3147, Val Corr X: 0.8847, Val Corr Y: 0.7987
Epoch [16/50], Train Loss: 0.2628, Val Loss: 0.2954, Val Corr X: 0.8870, Val Corr Y: 0.8060
Epoch [17/50], Train Loss: 0.2457, Val Loss: 0.2898, Val Corr X: 0.8904, Val Corr Y: 0.8103
Epoch [18/50], Train Loss: 0.2364, Val Loss: 0.2850, Val Corr X: 0.8914, Val Corr Y: 0.8149
Epoch [19/50], Train Loss: 0.2377, Val Loss: 0.2786, Val Corr X: 0.8948, Val Corr Y: 0.8148
Epoch [20/50], Train Loss: 0.2319, Val Loss: 0.2774, Val Corr X: 0.8955, Val Corr Y: 0.8191
Epoch [21/50], Train Loss: 0.2196, Val Loss: 0.2701, Val Corr X: 0.8972, Val Corr Y: 0.8222
Epoch [22/50], Train Loss: 0.2150, Val Loss: 0.2691, Val Corr X: 0.8995, Val Corr Y: 0.8223
Epoch [23/50], Train Loss: 0.2127, Val Loss: 0.2655, Val Corr X: 0.8996, Val Corr Y: 0.8267
Epoch [24/50], Train Loss: 0.2083, Val Loss: 0.2649, Val Corr X: 0.9014, Val Corr Y: 0.8294
Epoch [25/50], Train Loss: 0.2071, Val Loss: 0.2767, Val Corr X: 0.8977, Val Corr Y: 0.8288
Epoch [26/50], Train Loss: 0.2113, Val Loss: 0.2678, Val Corr X: 0.9004, Val Corr Y: 0.8327
Epoch [27/50], Train Loss: 0.2094, Val Loss: 0.2561, Val Corr X: 0.9035, Val Corr Y: 0.8326
Epoch [28/50], Train Loss: 0.1986, Val Loss: 0.2534, Val Corr X: 0.9050, Val Corr Y: 0.8355
Epoch [29/50], Train Loss: 0.1920, Val Loss: 0.2642, Val Corr X: 0.9063, Val Corr Y: 0.8345
Epoch [30/50], Train Loss: 0.2028, Val Loss: 0.2501, Val Corr X: 0.9064, Val Corr Y: 0.8373
Epoch [31/50], Train Loss: 0.1924, Val Loss: 0.2490, Val Corr X: 0.9074, Val Corr Y: 0.8351
Epoch [32/50], Train Loss: 0.1883, Val Loss: 0.2498, Val Corr X: 0.9078, Val Corr Y: 0.8405
Epoch [33/50], Train Loss: 0.1809, Val Loss: 0.2514, Val Corr X: 0.9074, Val Corr Y: 0.8372
Epoch [34/50], Train Loss: 0.1815, Val Loss: 0.2455, Val Corr X: 0.9094, Val Corr Y: 0.8416
Epoch [35/50], Train Loss: 0.1752, Val Loss: 0.2463, Val Corr X: 0.9096, Val Corr Y: 0.8407
Epoch [36/50], Train Loss: 0.1707, Val Loss: 0.2425, Val Corr X: 0.9094, Val Corr Y: 0.8427
Epoch [37/50], Train Loss: 0.1767, Val Loss: 0.2489, Val Corr X: 0.9109, Val Corr Y: 0.8422
Epoch [38/50], Train Loss: 0.1702, Val Loss: 0.2414, Val Corr X: 0.9116, Val Corr Y: 0.8427
Epoch [39/50], Train Loss: 0.1702, Val Loss: 0.2480, Val Corr X: 0.9104, Val Corr Y: 0.8421
Epoch [40/50], Train Loss: 0.1748, Val Loss: 0.2517, Val Corr X: 0.9124, Val Corr Y: 0.8403
Epoch [41/50], Train Loss: 0.1695, Val Loss: 0.2483, Val Corr X: 0.9132, Val Corr Y: 0.8445
Epoch [42/50], Train Loss: 0.1813, Val Loss: 0.2393, Val Corr X: 0.9136, Val Corr Y: 0.8447
Epoch [43/50], Train Loss: 0.1839, Val Loss: 0.2437, Val Corr X: 0.9139, Val Corr Y: 0.8443
Epoch [44/50], Train Loss: 0.1711, Val Loss: 0.2432, Val Corr X: 0.9140, Val Corr Y: 0.8474
Epoch [45/50], Train Loss: 0.1649, Val Loss: 0.2347, Val Corr X: 0.9144, Val Corr Y: 0.8499
Epoch [46/50], Train Loss: 0.1595, Val Loss: 0.2325, Val Corr X: 0.9136, Val Corr Y: 0.8530
Epoch [47/50], Train Loss: 0.1562, Val Loss: 0.2318, Val Corr X: 0.9158, Val Corr Y: 0.8508
Epoch [48/50], Train Loss: 0.1529, Val Loss: 0.2351, Val Corr X: 0.9159, Val Corr Y: 0.8501
Epoch [49/50], Train Loss: 0.1572, Val Loss: 0.2258, Val Corr X: 0.9179, Val Corr Y: 0.8508
Epoch [50/50], Train Loss: 0.1565, Val Loss: 0.2336, Val Corr X: 0.9171, Val Corr Y: 0.8479
Model saved at snn_mcmaze_split_3.pth. Exiting training loop.

--- Evaluating on Test Set for Split 3 ---
Loading model from snn_mcmaze_split_3.pth for testing...

Test Set Results (Split 3):
  Loss: 0.2253
  Correlation X: 0.9085
  Correlation Y: 0.8567
--------------------------

--- Split 4/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [49.836723  9.764423], Vel Std (local): [339.36877 292.42065]

Split 4 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 4...
Using device: cuda
Epoch [1/50], Train Loss: 1.0088, Val Loss: 0.8521, Val Corr X: 0.5183, Val Corr Y: 0.4973
Epoch [2/50], Train Loss: 0.8115, Val Loss: 0.6582, Val Corr X: 0.6802, Val Corr Y: 0.5651
Epoch [3/50], Train Loss: 0.6096, Val Loss: 0.5241, Val Corr X: 0.7532, Val Corr Y: 0.6375
Epoch [4/50], Train Loss: 0.5411, Val Loss: 0.4756, Val Corr X: 0.7859, Val Corr Y: 0.6647
Epoch [5/50], Train Loss: 0.4823, Val Loss: 0.4415, Val Corr X: 0.8017, Val Corr Y: 0.6876
Epoch [6/50], Train Loss: 0.4383, Val Loss: 0.4183, Val Corr X: 0.8189, Val Corr Y: 0.7109
Epoch [7/50], Train Loss: 0.4035, Val Loss: 0.3788, Val Corr X: 0.8276, Val Corr Y: 0.7445
Epoch [8/50], Train Loss: 0.3825, Val Loss: 0.3708, Val Corr X: 0.8326, Val Corr Y: 0.7566
Epoch [9/50], Train Loss: 0.3545, Val Loss: 0.3495, Val Corr X: 0.8404, Val Corr Y: 0.7668
Epoch [10/50], Train Loss: 0.3393, Val Loss: 0.3430, Val Corr X: 0.8465, Val Corr Y: 0.7772
Epoch [11/50], Train Loss: 0.3217, Val Loss: 0.3327, Val Corr X: 0.8515, Val Corr Y: 0.7884
Epoch [12/50], Train Loss: 0.3081, Val Loss: 0.3143, Val Corr X: 0.8576, Val Corr Y: 0.7973
Epoch [13/50], Train Loss: 0.2981, Val Loss: 0.3016, Val Corr X: 0.8619, Val Corr Y: 0.8041
Epoch [14/50], Train Loss: 0.2804, Val Loss: 0.2906, Val Corr X: 0.8662, Val Corr Y: 0.8109
Epoch [15/50], Train Loss: 0.2710, Val Loss: 0.2879, Val Corr X: 0.8695, Val Corr Y: 0.8162
Epoch [16/50], Train Loss: 0.2718, Val Loss: 0.2816, Val Corr X: 0.8733, Val Corr Y: 0.8189
Epoch [17/50], Train Loss: 0.2626, Val Loss: 0.2855, Val Corr X: 0.8762, Val Corr Y: 0.8230
Epoch [18/50], Train Loss: 0.2496, Val Loss: 0.2695, Val Corr X: 0.8781, Val Corr Y: 0.8266
Epoch [19/50], Train Loss: 0.2384, Val Loss: 0.2690, Val Corr X: 0.8792, Val Corr Y: 0.8284
Epoch [20/50], Train Loss: 0.2263, Val Loss: 0.2627, Val Corr X: 0.8818, Val Corr Y: 0.8331
Epoch [21/50], Train Loss: 0.2263, Val Loss: 0.2590, Val Corr X: 0.8853, Val Corr Y: 0.8337
Epoch [22/50], Train Loss: 0.2204, Val Loss: 0.2587, Val Corr X: 0.8863, Val Corr Y: 0.8351
Epoch [23/50], Train Loss: 0.2239, Val Loss: 0.2610, Val Corr X: 0.8886, Val Corr Y: 0.8367
Epoch [24/50], Train Loss: 0.2089, Val Loss: 0.2473, Val Corr X: 0.8897, Val Corr Y: 0.8410
Epoch [25/50], Train Loss: 0.2025, Val Loss: 0.2476, Val Corr X: 0.8896, Val Corr Y: 0.8411
Epoch [26/50], Train Loss: 0.1993, Val Loss: 0.2466, Val Corr X: 0.8908, Val Corr Y: 0.8426
Epoch [27/50], Train Loss: 0.2092, Val Loss: 0.2808, Val Corr X: 0.8927, Val Corr Y: 0.8333
Epoch [28/50], Train Loss: 0.2027, Val Loss: 0.2485, Val Corr X: 0.8929, Val Corr Y: 0.8456
Epoch [29/50], Train Loss: 0.1945, Val Loss: 0.2446, Val Corr X: 0.8942, Val Corr Y: 0.8472
Epoch [30/50], Train Loss: 0.1910, Val Loss: 0.2467, Val Corr X: 0.8948, Val Corr Y: 0.8476
Epoch [31/50], Train Loss: 0.1878, Val Loss: 0.2392, Val Corr X: 0.8948, Val Corr Y: 0.8502
Epoch [32/50], Train Loss: 0.1893, Val Loss: 0.2374, Val Corr X: 0.8975, Val Corr Y: 0.8511
Epoch [33/50], Train Loss: 0.1801, Val Loss: 0.2318, Val Corr X: 0.8983, Val Corr Y: 0.8529
Epoch [34/50], Train Loss: 0.1748, Val Loss: 0.2310, Val Corr X: 0.8987, Val Corr Y: 0.8521
Epoch [35/50], Train Loss: 0.1716, Val Loss: 0.2349, Val Corr X: 0.8991, Val Corr Y: 0.8525
Epoch [36/50], Train Loss: 0.1764, Val Loss: 0.2259, Val Corr X: 0.8996, Val Corr Y: 0.8549
Epoch [37/50], Train Loss: 0.1687, Val Loss: 0.2322, Val Corr X: 0.8984, Val Corr Y: 0.8556
Epoch [38/50], Train Loss: 0.1683, Val Loss: 0.2295, Val Corr X: 0.8995, Val Corr Y: 0.8536
Epoch [39/50], Train Loss: 0.1647, Val Loss: 0.2349, Val Corr X: 0.9008, Val Corr Y: 0.8534
Epoch [40/50], Train Loss: 0.1687, Val Loss: 0.2311, Val Corr X: 0.9011, Val Corr Y: 0.8544
Epoch [41/50], Train Loss: 0.1641, Val Loss: 0.2276, Val Corr X: 0.9016, Val Corr Y: 0.8577
Epoch [42/50], Train Loss: 0.1621, Val Loss: 0.2221, Val Corr X: 0.9029, Val Corr Y: 0.8577
Epoch [43/50], Train Loss: 0.1588, Val Loss: 0.2204, Val Corr X: 0.9032, Val Corr Y: 0.8575
Epoch [44/50], Train Loss: 0.1651, Val Loss: 0.3036, Val Corr X: 0.9031, Val Corr Y: 0.8367
Epoch [45/50], Train Loss: 0.2376, Val Loss: 0.3160, Val Corr X: 0.8965, Val Corr Y: 0.8405
Epoch [46/50], Train Loss: 0.2211, Val Loss: 0.2501, Val Corr X: 0.8988, Val Corr Y: 0.8460
Epoch [47/50], Train Loss: 0.1989, Val Loss: 0.2686, Val Corr X: 0.8953, Val Corr Y: 0.8403
Epoch [48/50], Train Loss: 0.1976, Val Loss: 0.2242, Val Corr X: 0.9027, Val Corr Y: 0.8574
Epoch [49/50], Train Loss: 0.1745, Val Loss: 0.2215, Val Corr X: 0.9057, Val Corr Y: 0.8578
Epoch [50/50], Train Loss: 0.1721, Val Loss: 0.2167, Val Corr X: 0.9066, Val Corr Y: 0.8610
Model saved at snn_mcmaze_split_4.pth. Exiting training loop.

--- Evaluating on Test Set for Split 4 ---
Loading model from snn_mcmaze_split_4.pth for testing...

Test Set Results (Split 4):
  Loss: 0.2241
  Correlation X: 0.9084
  Correlation Y: 0.8542
--------------------------

--- Split 5/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [53.494976   5.2766104], Vel Std (local): [338.46353 291.7812 ]

Split 5 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 5...
Using device: cuda
Epoch [1/50], Train Loss: 0.9761, Val Loss: 0.8260, Val Corr X: 0.5399, Val Corr Y: 0.4985
Epoch [2/50], Train Loss: 0.7159, Val Loss: 0.6248, Val Corr X: 0.7338, Val Corr Y: 0.5977
Epoch [3/50], Train Loss: 0.6112, Val Loss: 0.5160, Val Corr X: 0.7734, Val Corr Y: 0.6463
Epoch [4/50], Train Loss: 0.5101, Val Loss: 0.5035, Val Corr X: 0.7908, Val Corr Y: 0.6591
Epoch [5/50], Train Loss: 0.4906, Val Loss: 0.4705, Val Corr X: 0.8057, Val Corr Y: 0.6830
Epoch [6/50], Train Loss: 0.4334, Val Loss: 0.4389, Val Corr X: 0.8260, Val Corr Y: 0.7104
Epoch [7/50], Train Loss: 0.4176, Val Loss: 0.3968, Val Corr X: 0.8329, Val Corr Y: 0.7284
Epoch [8/50], Train Loss: 0.3785, Val Loss: 0.3928, Val Corr X: 0.8382, Val Corr Y: 0.7436
Epoch [9/50], Train Loss: 0.3623, Val Loss: 0.3613, Val Corr X: 0.8483, Val Corr Y: 0.7593
Epoch [10/50], Train Loss: 0.3378, Val Loss: 0.3517, Val Corr X: 0.8554, Val Corr Y: 0.7675
Epoch [11/50], Train Loss: 0.3223, Val Loss: 0.3395, Val Corr X: 0.8595, Val Corr Y: 0.7801
Epoch [12/50], Train Loss: 0.3096, Val Loss: 0.3242, Val Corr X: 0.8638, Val Corr Y: 0.7892
Epoch [13/50], Train Loss: 0.2903, Val Loss: 0.3132, Val Corr X: 0.8703, Val Corr Y: 0.7969
Epoch [14/50], Train Loss: 0.2783, Val Loss: 0.3030, Val Corr X: 0.8745, Val Corr Y: 0.8041
Epoch [15/50], Train Loss: 0.2694, Val Loss: 0.2957, Val Corr X: 0.8793, Val Corr Y: 0.8104
Epoch [16/50], Train Loss: 0.2734, Val Loss: 0.2874, Val Corr X: 0.8834, Val Corr Y: 0.8156
Epoch [17/50], Train Loss: 0.2590, Val Loss: 0.2770, Val Corr X: 0.8855, Val Corr Y: 0.8248
Epoch [18/50], Train Loss: 0.2503, Val Loss: 0.2742, Val Corr X: 0.8873, Val Corr Y: 0.8285
Epoch [19/50], Train Loss: 0.2430, Val Loss: 0.2703, Val Corr X: 0.8903, Val Corr Y: 0.8306
Epoch [20/50], Train Loss: 0.2324, Val Loss: 0.2608, Val Corr X: 0.8925, Val Corr Y: 0.8355
Epoch [21/50], Train Loss: 0.2240, Val Loss: 0.2596, Val Corr X: 0.8949, Val Corr Y: 0.8363
Epoch [22/50], Train Loss: 0.2181, Val Loss: 0.2521, Val Corr X: 0.8955, Val Corr Y: 0.8400
Epoch [23/50], Train Loss: 0.2095, Val Loss: 0.2489, Val Corr X: 0.8970, Val Corr Y: 0.8412
Epoch [24/50], Train Loss: 0.2041, Val Loss: 0.2489, Val Corr X: 0.8986, Val Corr Y: 0.8442
Epoch [25/50], Train Loss: 0.2086, Val Loss: 0.2577, Val Corr X: 0.8989, Val Corr Y: 0.8384
Epoch [26/50], Train Loss: 0.1999, Val Loss: 0.2529, Val Corr X: 0.9002, Val Corr Y: 0.8425
Epoch [27/50], Train Loss: 0.2009, Val Loss: 0.2438, Val Corr X: 0.9019, Val Corr Y: 0.8457
Epoch [28/50], Train Loss: 0.1981, Val Loss: 0.2402, Val Corr X: 0.9029, Val Corr Y: 0.8477
Epoch [29/50], Train Loss: 0.1947, Val Loss: 0.2500, Val Corr X: 0.9012, Val Corr Y: 0.8490
Epoch [30/50], Train Loss: 0.1895, Val Loss: 0.2409, Val Corr X: 0.9036, Val Corr Y: 0.8522
Epoch [31/50], Train Loss: 0.1900, Val Loss: 0.2375, Val Corr X: 0.9054, Val Corr Y: 0.8524
Epoch [32/50], Train Loss: 0.1920, Val Loss: 0.2361, Val Corr X: 0.9046, Val Corr Y: 0.8529
Epoch [33/50], Train Loss: 0.1779, Val Loss: 0.2349, Val Corr X: 0.9058, Val Corr Y: 0.8553
Epoch [34/50], Train Loss: 0.1766, Val Loss: 0.2273, Val Corr X: 0.9080, Val Corr Y: 0.8560
Epoch [35/50], Train Loss: 0.1739, Val Loss: 0.2308, Val Corr X: 0.9066, Val Corr Y: 0.8561
Epoch [36/50], Train Loss: 0.1705, Val Loss: 0.2377, Val Corr X: 0.9084, Val Corr Y: 0.8544
Epoch [37/50], Train Loss: 0.1807, Val Loss: 0.2462, Val Corr X: 0.9103, Val Corr Y: 0.8496
Epoch [38/50], Train Loss: 0.1740, Val Loss: 0.2236, Val Corr X: 0.9111, Val Corr Y: 0.8578
Epoch [39/50], Train Loss: 0.1687, Val Loss: 0.2218, Val Corr X: 0.9108, Val Corr Y: 0.8611
Epoch [40/50], Train Loss: 0.1667, Val Loss: 0.2389, Val Corr X: 0.9120, Val Corr Y: 0.8541
Epoch [41/50], Train Loss: 0.1801, Val Loss: 0.2170, Val Corr X: 0.9143, Val Corr Y: 0.8598
Epoch [42/50], Train Loss: 0.1735, Val Loss: 0.2268, Val Corr X: 0.9128, Val Corr Y: 0.8578
Epoch [43/50], Train Loss: 0.1725, Val Loss: 0.2315, Val Corr X: 0.9117, Val Corr Y: 0.8609
Epoch [44/50], Train Loss: 0.1723, Val Loss: 0.2237, Val Corr X: 0.9152, Val Corr Y: 0.8600
Epoch [45/50], Train Loss: 0.1728, Val Loss: 0.2292, Val Corr X: 0.9131, Val Corr Y: 0.8569
Epoch [46/50], Train Loss: 0.1707, Val Loss: 0.2240, Val Corr X: 0.9141, Val Corr Y: 0.8635
Epoch [47/50], Train Loss: 0.1619, Val Loss: 0.2120, Val Corr X: 0.9167, Val Corr Y: 0.8642
Epoch [48/50], Train Loss: 0.1543, Val Loss: 0.2168, Val Corr X: 0.9157, Val Corr Y: 0.8630
Epoch [49/50], Train Loss: 0.1574, Val Loss: 0.2217, Val Corr X: 0.9174, Val Corr Y: 0.8606
Epoch [50/50], Train Loss: 0.1643, Val Loss: 0.2166, Val Corr X: 0.9182, Val Corr Y: 0.8591
Model saved at snn_mcmaze_split_5.pth. Exiting training loop.

--- Evaluating on Test Set for Split 5 ---
Loading model from snn_mcmaze_split_5.pth for testing...

Test Set Results (Split 5):
  Loss: 0.2112
  Correlation X: 0.9153
  Correlation Y: 0.8580
--------------------------

--- Split 6/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [50.041023 10.620351], Vel Std (local): [340.8734  289.92502]

Split 6 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 6...
Using device: cuda
Epoch [1/50], Train Loss: 0.9035, Val Loss: 0.6927, Val Corr X: 0.6900, Val Corr Y: 0.4979
Epoch [2/50], Train Loss: 0.6713, Val Loss: 0.5986, Val Corr X: 0.7359, Val Corr Y: 0.5508
Epoch [3/50], Train Loss: 0.5705, Val Loss: 0.5427, Val Corr X: 0.7703, Val Corr Y: 0.6027
Epoch [4/50], Train Loss: 0.4998, Val Loss: 0.4913, Val Corr X: 0.7951, Val Corr Y: 0.6529
Epoch [5/50], Train Loss: 0.4431, Val Loss: 0.4466, Val Corr X: 0.8048, Val Corr Y: 0.6882
Epoch [6/50], Train Loss: 0.4130, Val Loss: 0.4095, Val Corr X: 0.8201, Val Corr Y: 0.7215
Epoch [7/50], Train Loss: 0.3869, Val Loss: 0.3869, Val Corr X: 0.8338, Val Corr Y: 0.7416
Epoch [8/50], Train Loss: 0.3494, Val Loss: 0.3720, Val Corr X: 0.8417, Val Corr Y: 0.7574
Epoch [9/50], Train Loss: 0.3340, Val Loss: 0.3473, Val Corr X: 0.8508, Val Corr Y: 0.7747
Epoch [10/50], Train Loss: 0.3232, Val Loss: 0.3365, Val Corr X: 0.8571, Val Corr Y: 0.7847
Epoch [11/50], Train Loss: 0.3052, Val Loss: 0.3179, Val Corr X: 0.8662, Val Corr Y: 0.7944
Epoch [12/50], Train Loss: 0.2967, Val Loss: 0.3057, Val Corr X: 0.8702, Val Corr Y: 0.8044
Epoch [13/50], Train Loss: 0.2752, Val Loss: 0.3004, Val Corr X: 0.8755, Val Corr Y: 0.8081
Epoch [14/50], Train Loss: 0.2633, Val Loss: 0.2913, Val Corr X: 0.8775, Val Corr Y: 0.8146
Epoch [15/50], Train Loss: 0.2551, Val Loss: 0.2865, Val Corr X: 0.8836, Val Corr Y: 0.8197
Epoch [16/50], Train Loss: 0.2590, Val Loss: 0.2820, Val Corr X: 0.8809, Val Corr Y: 0.8240
Epoch [17/50], Train Loss: 0.2397, Val Loss: 0.2716, Val Corr X: 0.8886, Val Corr Y: 0.8273
Epoch [18/50], Train Loss: 0.2352, Val Loss: 0.2686, Val Corr X: 0.8883, Val Corr Y: 0.8315
Epoch [19/50], Train Loss: 0.2364, Val Loss: 0.2675, Val Corr X: 0.8910, Val Corr Y: 0.8318
Epoch [20/50], Train Loss: 0.2261, Val Loss: 0.2569, Val Corr X: 0.8940, Val Corr Y: 0.8347
Epoch [21/50], Train Loss: 0.2177, Val Loss: 0.2628, Val Corr X: 0.8949, Val Corr Y: 0.8335
Epoch [22/50], Train Loss: 0.2226, Val Loss: 0.2508, Val Corr X: 0.8975, Val Corr Y: 0.8390
Epoch [23/50], Train Loss: 0.2151, Val Loss: 0.2565, Val Corr X: 0.8969, Val Corr Y: 0.8394
Epoch [24/50], Train Loss: 0.2108, Val Loss: 0.2489, Val Corr X: 0.8995, Val Corr Y: 0.8417
Epoch [25/50], Train Loss: 0.2057, Val Loss: 0.2458, Val Corr X: 0.9004, Val Corr Y: 0.8421
Epoch [26/50], Train Loss: 0.2044, Val Loss: 0.2458, Val Corr X: 0.9007, Val Corr Y: 0.8404
Epoch [27/50], Train Loss: 0.1948, Val Loss: 0.2466, Val Corr X: 0.9018, Val Corr Y: 0.8424
Epoch [28/50], Train Loss: 0.1942, Val Loss: 0.2484, Val Corr X: 0.9021, Val Corr Y: 0.8414
Epoch [29/50], Train Loss: 0.1939, Val Loss: 0.2444, Val Corr X: 0.9022, Val Corr Y: 0.8454
Epoch [30/50], Train Loss: 0.1831, Val Loss: 0.2379, Val Corr X: 0.9047, Val Corr Y: 0.8484
Epoch [31/50], Train Loss: 0.1836, Val Loss: 0.2423, Val Corr X: 0.9047, Val Corr Y: 0.8439
Epoch [32/50], Train Loss: 0.1817, Val Loss: 0.2391, Val Corr X: 0.9049, Val Corr Y: 0.8489
Epoch [33/50], Train Loss: 0.1795, Val Loss: 0.2503, Val Corr X: 0.9057, Val Corr Y: 0.8480
Epoch [34/50], Train Loss: 0.1967, Val Loss: 0.2451, Val Corr X: 0.9047, Val Corr Y: 0.8486
Epoch [35/50], Train Loss: 0.1894, Val Loss: 0.2326, Val Corr X: 0.9073, Val Corr Y: 0.8536
Epoch [36/50], Train Loss: 0.1794, Val Loss: 0.2282, Val Corr X: 0.9107, Val Corr Y: 0.8513
Epoch [37/50], Train Loss: 0.1736, Val Loss: 0.2377, Val Corr X: 0.9100, Val Corr Y: 0.8497
Epoch [38/50], Train Loss: 0.1766, Val Loss: 0.2289, Val Corr X: 0.9105, Val Corr Y: 0.8546
Epoch [39/50], Train Loss: 0.1705, Val Loss: 0.2240, Val Corr X: 0.9107, Val Corr Y: 0.8557
Epoch [40/50], Train Loss: 0.1667, Val Loss: 0.2265, Val Corr X: 0.9120, Val Corr Y: 0.8546
Epoch [41/50], Train Loss: 0.1731, Val Loss: 0.2274, Val Corr X: 0.9117, Val Corr Y: 0.8541
Epoch [42/50], Train Loss: 0.1653, Val Loss: 0.2316, Val Corr X: 0.9116, Val Corr Y: 0.8541
Epoch [43/50], Train Loss: 0.1664, Val Loss: 0.2220, Val Corr X: 0.9140, Val Corr Y: 0.8562
Epoch [44/50], Train Loss: 0.1574, Val Loss: 0.2226, Val Corr X: 0.9131, Val Corr Y: 0.8579
Epoch [45/50], Train Loss: 0.1565, Val Loss: 0.2230, Val Corr X: 0.9130, Val Corr Y: 0.8585
Epoch [46/50], Train Loss: 0.1593, Val Loss: 0.2226, Val Corr X: 0.9144, Val Corr Y: 0.8562
Epoch [47/50], Train Loss: 0.1544, Val Loss: 0.2290, Val Corr X: 0.9135, Val Corr Y: 0.8577
Epoch [48/50], Train Loss: 0.1665, Val Loss: 0.2446, Val Corr X: 0.9132, Val Corr Y: 0.8559
Epoch [49/50], Train Loss: 0.1793, Val Loss: 0.2203, Val Corr X: 0.9161, Val Corr Y: 0.8583
Epoch [50/50], Train Loss: 0.1614, Val Loss: 0.2362, Val Corr X: 0.9150, Val Corr Y: 0.8549
Model saved at snn_mcmaze_split_6.pth. Exiting training loop.

--- Evaluating on Test Set for Split 6 ---
Loading model from snn_mcmaze_split_6.pth for testing...

Test Set Results (Split 6):
  Loss: 0.2436
  Correlation X: 0.9083
  Correlation Y: 0.8514
--------------------------

--- Split 7/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [55.053783   1.7343905], Vel Std (local): [340.7456 290.3352]

Split 7 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 7...
Using device: cuda
Epoch [1/50], Train Loss: 0.9267, Val Loss: 0.7849, Val Corr X: 0.6428, Val Corr Y: 0.4457
Epoch [2/50], Train Loss: 0.6934, Val Loss: 0.6350, Val Corr X: 0.7296, Val Corr Y: 0.5543
Epoch [3/50], Train Loss: 0.5614, Val Loss: 0.5419, Val Corr X: 0.7628, Val Corr Y: 0.6122
Epoch [4/50], Train Loss: 0.4986, Val Loss: 0.5088, Val Corr X: 0.7881, Val Corr Y: 0.6479
Epoch [5/50], Train Loss: 0.4463, Val Loss: 0.4709, Val Corr X: 0.8050, Val Corr Y: 0.6839
Epoch [6/50], Train Loss: 0.4188, Val Loss: 0.4191, Val Corr X: 0.8221, Val Corr Y: 0.7122
Epoch [7/50], Train Loss: 0.3860, Val Loss: 0.4150, Val Corr X: 0.8305, Val Corr Y: 0.7238
Epoch [8/50], Train Loss: 0.3668, Val Loss: 0.3980, Val Corr X: 0.8353, Val Corr Y: 0.7425
Epoch [9/50], Train Loss: 0.3419, Val Loss: 0.3719, Val Corr X: 0.8470, Val Corr Y: 0.7548
Epoch [10/50], Train Loss: 0.3256, Val Loss: 0.3546, Val Corr X: 0.8520, Val Corr Y: 0.7678
Epoch [11/50], Train Loss: 0.3114, Val Loss: 0.3569, Val Corr X: 0.8517, Val Corr Y: 0.7735
Epoch [12/50], Train Loss: 0.3028, Val Loss: 0.3308, Val Corr X: 0.8613, Val Corr Y: 0.7869
Epoch [13/50], Train Loss: 0.2845, Val Loss: 0.3189, Val Corr X: 0.8664, Val Corr Y: 0.7926
Epoch [14/50], Train Loss: 0.2709, Val Loss: 0.3148, Val Corr X: 0.8684, Val Corr Y: 0.7957
Epoch [15/50], Train Loss: 0.2684, Val Loss: 0.3222, Val Corr X: 0.8733, Val Corr Y: 0.8012
Epoch [16/50], Train Loss: 0.2621, Val Loss: 0.3053, Val Corr X: 0.8766, Val Corr Y: 0.8092
Epoch [17/50], Train Loss: 0.2513, Val Loss: 0.3024, Val Corr X: 0.8789, Val Corr Y: 0.8137
Epoch [18/50], Train Loss: 0.2528, Val Loss: 0.2936, Val Corr X: 0.8795, Val Corr Y: 0.8150
Epoch [19/50], Train Loss: 0.2391, Val Loss: 0.2860, Val Corr X: 0.8821, Val Corr Y: 0.8200
Epoch [20/50], Train Loss: 0.2259, Val Loss: 0.2779, Val Corr X: 0.8859, Val Corr Y: 0.8225
Epoch [21/50], Train Loss: 0.2210, Val Loss: 0.2738, Val Corr X: 0.8871, Val Corr Y: 0.8245
Epoch [22/50], Train Loss: 0.2134, Val Loss: 0.2696, Val Corr X: 0.8896, Val Corr Y: 0.8264
Epoch [23/50], Train Loss: 0.2075, Val Loss: 0.2699, Val Corr X: 0.8896, Val Corr Y: 0.8287
Epoch [24/50], Train Loss: 0.2244, Val Loss: 0.3792, Val Corr X: 0.8887, Val Corr Y: 0.8015
Epoch [25/50], Train Loss: 0.2789, Val Loss: 0.2713, Val Corr X: 0.8919, Val Corr Y: 0.8307
Epoch [26/50], Train Loss: 0.2273, Val Loss: 0.3007, Val Corr X: 0.8896, Val Corr Y: 0.8125
Epoch [27/50], Train Loss: 0.2311, Val Loss: 0.2741, Val Corr X: 0.8924, Val Corr Y: 0.8285
Epoch [28/50], Train Loss: 0.2167, Val Loss: 0.2642, Val Corr X: 0.8933, Val Corr Y: 0.8315
Epoch [29/50], Train Loss: 0.2041, Val Loss: 0.2672, Val Corr X: 0.8934, Val Corr Y: 0.8316
Epoch [30/50], Train Loss: 0.1980, Val Loss: 0.2605, Val Corr X: 0.8946, Val Corr Y: 0.8361
Epoch [31/50], Train Loss: 0.1974, Val Loss: 0.2607, Val Corr X: 0.8944, Val Corr Y: 0.8376
Epoch [32/50], Train Loss: 0.1911, Val Loss: 0.2530, Val Corr X: 0.8981, Val Corr Y: 0.8397
Epoch [33/50], Train Loss: 0.1866, Val Loss: 0.2516, Val Corr X: 0.8972, Val Corr Y: 0.8404
Epoch [34/50], Train Loss: 0.1857, Val Loss: 0.2504, Val Corr X: 0.8982, Val Corr Y: 0.8415
Epoch [35/50], Train Loss: 0.1788, Val Loss: 0.2502, Val Corr X: 0.8972, Val Corr Y: 0.8418
Epoch [36/50], Train Loss: 0.1780, Val Loss: 0.2471, Val Corr X: 0.8998, Val Corr Y: 0.8419
Epoch [37/50], Train Loss: 0.1747, Val Loss: 0.2457, Val Corr X: 0.9002, Val Corr Y: 0.8429
Epoch [38/50], Train Loss: 0.1727, Val Loss: 0.2428, Val Corr X: 0.9000, Val Corr Y: 0.8455
Epoch [39/50], Train Loss: 0.1722, Val Loss: 0.2445, Val Corr X: 0.9015, Val Corr Y: 0.8453
Epoch [40/50], Train Loss: 0.1668, Val Loss: 0.2443, Val Corr X: 0.9014, Val Corr Y: 0.8441
Epoch [41/50], Train Loss: 0.1717, Val Loss: 0.2509, Val Corr X: 0.9016, Val Corr Y: 0.8449
Epoch [42/50], Train Loss: 0.1677, Val Loss: 0.2423, Val Corr X: 0.9019, Val Corr Y: 0.8478
Epoch [43/50], Train Loss: 0.1683, Val Loss: 0.2389, Val Corr X: 0.9031, Val Corr Y: 0.8483
Epoch [44/50], Train Loss: 0.1616, Val Loss: 0.2402, Val Corr X: 0.9044, Val Corr Y: 0.8485
Epoch [45/50], Train Loss: 0.1644, Val Loss: 0.2366, Val Corr X: 0.9052, Val Corr Y: 0.8501
Epoch [46/50], Train Loss: 0.1648, Val Loss: 0.2452, Val Corr X: 0.9050, Val Corr Y: 0.8462
Epoch [47/50], Train Loss: 0.1586, Val Loss: 0.2413, Val Corr X: 0.9053, Val Corr Y: 0.8501
Epoch [48/50], Train Loss: 0.1577, Val Loss: 0.2376, Val Corr X: 0.9072, Val Corr Y: 0.8511
Epoch [49/50], Train Loss: 0.1692, Val Loss: 0.2453, Val Corr X: 0.9069, Val Corr Y: 0.8465
Epoch [50/50], Train Loss: 0.1683, Val Loss: 0.2573, Val Corr X: 0.9077, Val Corr Y: 0.8428
Model saved at snn_mcmaze_split_7.pth. Exiting training loop.

--- Evaluating on Test Set for Split 7 ---
Loading model from snn_mcmaze_split_7.pth for testing...

Test Set Results (Split 7):
  Loss: 0.2459
  Correlation X: 0.9020
  Correlation Y: 0.8574
--------------------------

--- Split 8/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [54.790928  6.571785], Vel Std (local): [340.45917 291.03302]

Split 8 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 8...
Using device: cuda
Epoch [1/50], Train Loss: 0.8253, Val Loss: 1.1390, Val Corr X: 0.5687, Val Corr Y: 0.5861
Epoch [2/50], Train Loss: 0.8186, Val Loss: 0.7024, Val Corr X: 0.6986, Val Corr Y: 0.5719
Epoch [3/50], Train Loss: 0.6532, Val Loss: 0.6289, Val Corr X: 0.7143, Val Corr Y: 0.6161
Epoch [4/50], Train Loss: 0.6124, Val Loss: 0.5510, Val Corr X: 0.7417, Val Corr Y: 0.6646
Epoch [5/50], Train Loss: 0.5065, Val Loss: 0.5081, Val Corr X: 0.7825, Val Corr Y: 0.7011
Epoch [6/50], Train Loss: 0.4501, Val Loss: 0.4818, Val Corr X: 0.7987, Val Corr Y: 0.7145
Epoch [7/50], Train Loss: 0.4215, Val Loss: 0.4393, Val Corr X: 0.8175, Val Corr Y: 0.7218
Epoch [8/50], Train Loss: 0.3957, Val Loss: 0.3981, Val Corr X: 0.8251, Val Corr Y: 0.7444
Epoch [9/50], Train Loss: 0.3699, Val Loss: 0.3682, Val Corr X: 0.8366, Val Corr Y: 0.7588
Epoch [10/50], Train Loss: 0.3493, Val Loss: 0.3521, Val Corr X: 0.8441, Val Corr Y: 0.7707
Epoch [11/50], Train Loss: 0.3314, Val Loss: 0.3415, Val Corr X: 0.8495, Val Corr Y: 0.7799
Epoch [12/50], Train Loss: 0.3132, Val Loss: 0.3283, Val Corr X: 0.8569, Val Corr Y: 0.7873
Epoch [13/50], Train Loss: 0.3020, Val Loss: 0.3230, Val Corr X: 0.8605, Val Corr Y: 0.7940
Epoch [14/50], Train Loss: 0.2883, Val Loss: 0.3128, Val Corr X: 0.8652, Val Corr Y: 0.7978
Epoch [15/50], Train Loss: 0.2773, Val Loss: 0.3021, Val Corr X: 0.8692, Val Corr Y: 0.8057
Epoch [16/50], Train Loss: 0.2605, Val Loss: 0.2970, Val Corr X: 0.8719, Val Corr Y: 0.8114
Epoch [17/50], Train Loss: 0.2497, Val Loss: 0.2872, Val Corr X: 0.8771, Val Corr Y: 0.8156
Epoch [18/50], Train Loss: 0.2536, Val Loss: 0.2850, Val Corr X: 0.8790, Val Corr Y: 0.8197
Epoch [19/50], Train Loss: 0.2432, Val Loss: 0.2856, Val Corr X: 0.8825, Val Corr Y: 0.8208
Epoch [20/50], Train Loss: 0.2416, Val Loss: 0.2708, Val Corr X: 0.8839, Val Corr Y: 0.8269
Epoch [21/50], Train Loss: 0.2210, Val Loss: 0.2671, Val Corr X: 0.8868, Val Corr Y: 0.8288
Epoch [22/50], Train Loss: 0.2264, Val Loss: 0.2705, Val Corr X: 0.8875, Val Corr Y: 0.8273
Epoch [23/50], Train Loss: 0.2207, Val Loss: 0.2754, Val Corr X: 0.8897, Val Corr Y: 0.8300
Epoch [24/50], Train Loss: 0.2169, Val Loss: 0.2631, Val Corr X: 0.8917, Val Corr Y: 0.8338
Epoch [25/50], Train Loss: 0.2110, Val Loss: 0.2596, Val Corr X: 0.8930, Val Corr Y: 0.8373
Epoch [26/50], Train Loss: 0.2019, Val Loss: 0.2572, Val Corr X: 0.8941, Val Corr Y: 0.8382
Epoch [27/50], Train Loss: 0.2023, Val Loss: 0.2521, Val Corr X: 0.8959, Val Corr Y: 0.8400
Epoch [28/50], Train Loss: 0.1967, Val Loss: 0.2494, Val Corr X: 0.8957, Val Corr Y: 0.8419
Epoch [29/50], Train Loss: 0.1969, Val Loss: 0.2502, Val Corr X: 0.8950, Val Corr Y: 0.8437
Epoch [30/50], Train Loss: 0.1933, Val Loss: 0.2495, Val Corr X: 0.8973, Val Corr Y: 0.8444
Epoch [31/50], Train Loss: 0.1896, Val Loss: 0.2451, Val Corr X: 0.8983, Val Corr Y: 0.8467
Epoch [32/50], Train Loss: 0.1853, Val Loss: 0.2386, Val Corr X: 0.9006, Val Corr Y: 0.8493
Epoch [33/50], Train Loss: 0.1788, Val Loss: 0.2369, Val Corr X: 0.9006, Val Corr Y: 0.8488
Epoch [34/50], Train Loss: 0.1773, Val Loss: 0.2415, Val Corr X: 0.9001, Val Corr Y: 0.8485
Epoch [35/50], Train Loss: 0.1909, Val Loss: 0.2398, Val Corr X: 0.9007, Val Corr Y: 0.8511
Epoch [36/50], Train Loss: 0.1843, Val Loss: 0.2511, Val Corr X: 0.9029, Val Corr Y: 0.8468
Epoch [37/50], Train Loss: 0.1869, Val Loss: 0.2479, Val Corr X: 0.9013, Val Corr Y: 0.8501
Epoch [38/50], Train Loss: 0.1785, Val Loss: 0.2278, Val Corr X: 0.9044, Val Corr Y: 0.8569
Epoch [39/50], Train Loss: 0.1755, Val Loss: 0.2322, Val Corr X: 0.9048, Val Corr Y: 0.8544
Epoch [40/50], Train Loss: 0.1710, Val Loss: 0.2319, Val Corr X: 0.9053, Val Corr Y: 0.8557
Epoch [41/50], Train Loss: 0.1677, Val Loss: 0.2248, Val Corr X: 0.9067, Val Corr Y: 0.8567
Epoch [42/50], Train Loss: 0.1612, Val Loss: 0.2263, Val Corr X: 0.9078, Val Corr Y: 0.8559
Epoch [43/50], Train Loss: 0.1622, Val Loss: 0.2275, Val Corr X: 0.9070, Val Corr Y: 0.8565
Epoch [44/50], Train Loss: 0.1651, Val Loss: 0.2263, Val Corr X: 0.9066, Val Corr Y: 0.8582
Epoch [45/50], Train Loss: 0.1670, Val Loss: 0.2451, Val Corr X: 0.9071, Val Corr Y: 0.8511
Epoch [46/50], Train Loss: 0.1709, Val Loss: 0.2774, Val Corr X: 0.9088, Val Corr Y: 0.8410
Epoch [47/50], Train Loss: 0.1853, Val Loss: 0.2347, Val Corr X: 0.9094, Val Corr Y: 0.8543
Epoch [48/50], Train Loss: 0.1651, Val Loss: 0.2287, Val Corr X: 0.9100, Val Corr Y: 0.8544
Epoch [49/50], Train Loss: 0.1609, Val Loss: 0.2326, Val Corr X: 0.9078, Val Corr Y: 0.8575
Epoch [50/50], Train Loss: 0.1619, Val Loss: 0.2240, Val Corr X: 0.9117, Val Corr Y: 0.8584
Model saved at snn_mcmaze_split_8.pth. Exiting training loop.

--- Evaluating on Test Set for Split 8 ---
Loading model from snn_mcmaze_split_8.pth for testing...

Test Set Results (Split 8):
  Loss: 0.2293
  Correlation X: 0.9081
  Correlation Y: 0.8550
--------------------------

--- Split 9/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [51.21075   8.147584], Vel Std (local): [339.21634 291.49323]

Split 9 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 9...
Using device: cuda
Epoch [1/50], Train Loss: 0.8871, Val Loss: 0.7152, Val Corr X: 0.6555, Val Corr Y: 0.4646
Epoch [2/50], Train Loss: 0.6324, Val Loss: 0.6190, Val Corr X: 0.7338, Val Corr Y: 0.5884
Epoch [3/50], Train Loss: 0.5403, Val Loss: 0.5484, Val Corr X: 0.7710, Val Corr Y: 0.6383
Epoch [4/50], Train Loss: 0.4710, Val Loss: 0.4858, Val Corr X: 0.7903, Val Corr Y: 0.6764
Epoch [5/50], Train Loss: 0.4283, Val Loss: 0.4414, Val Corr X: 0.8120, Val Corr Y: 0.7113
Epoch [6/50], Train Loss: 0.3903, Val Loss: 0.4216, Val Corr X: 0.8237, Val Corr Y: 0.7320
Epoch [7/50], Train Loss: 0.3686, Val Loss: 0.3831, Val Corr X: 0.8319, Val Corr Y: 0.7528
Epoch [8/50], Train Loss: 0.3402, Val Loss: 0.3787, Val Corr X: 0.8382, Val Corr Y: 0.7690
Epoch [9/50], Train Loss: 0.3227, Val Loss: 0.3464, Val Corr X: 0.8498, Val Corr Y: 0.7833
Epoch [10/50], Train Loss: 0.3081, Val Loss: 0.3461, Val Corr X: 0.8557, Val Corr Y: 0.7889
Epoch [11/50], Train Loss: 0.2948, Val Loss: 0.3244, Val Corr X: 0.8607, Val Corr Y: 0.7986
Epoch [12/50], Train Loss: 0.2784, Val Loss: 0.3174, Val Corr X: 0.8618, Val Corr Y: 0.8080
Epoch [13/50], Train Loss: 0.2624, Val Loss: 0.3084, Val Corr X: 0.8666, Val Corr Y: 0.8137
Epoch [14/50], Train Loss: 0.2571, Val Loss: 0.2985, Val Corr X: 0.8722, Val Corr Y: 0.8154
Epoch [15/50], Train Loss: 0.2614, Val Loss: 0.3142, Val Corr X: 0.8735, Val Corr Y: 0.8156
Epoch [16/50], Train Loss: 0.2578, Val Loss: 0.2994, Val Corr X: 0.8778, Val Corr Y: 0.8211
Epoch [17/50], Train Loss: 0.2403, Val Loss: 0.3003, Val Corr X: 0.8769, Val Corr Y: 0.8221
Epoch [18/50], Train Loss: 0.2354, Val Loss: 0.2874, Val Corr X: 0.8819, Val Corr Y: 0.8266
Epoch [19/50], Train Loss: 0.2229, Val Loss: 0.2952, Val Corr X: 0.8845, Val Corr Y: 0.8275
Epoch [20/50], Train Loss: 0.2270, Val Loss: 0.2835, Val Corr X: 0.8865, Val Corr Y: 0.8293
Epoch [21/50], Train Loss: 0.2190, Val Loss: 0.2711, Val Corr X: 0.8852, Val Corr Y: 0.8354
Epoch [22/50], Train Loss: 0.2091, Val Loss: 0.2631, Val Corr X: 0.8883, Val Corr Y: 0.8393
Epoch [23/50], Train Loss: 0.1997, Val Loss: 0.2658, Val Corr X: 0.8907, Val Corr Y: 0.8356
Epoch [24/50], Train Loss: 0.2069, Val Loss: 0.2701, Val Corr X: 0.8905, Val Corr Y: 0.8388
Epoch [25/50], Train Loss: 0.2019, Val Loss: 0.2678, Val Corr X: 0.8921, Val Corr Y: 0.8376
Epoch [26/50], Train Loss: 0.2031, Val Loss: 0.2663, Val Corr X: 0.8932, Val Corr Y: 0.8396
Epoch [27/50], Train Loss: 0.2032, Val Loss: 0.2562, Val Corr X: 0.8929, Val Corr Y: 0.8437
Epoch [28/50], Train Loss: 0.1950, Val Loss: 0.2497, Val Corr X: 0.8967, Val Corr Y: 0.8477
Epoch [29/50], Train Loss: 0.1869, Val Loss: 0.2513, Val Corr X: 0.8976, Val Corr Y: 0.8469
Epoch [30/50], Train Loss: 0.1807, Val Loss: 0.2432, Val Corr X: 0.8982, Val Corr Y: 0.8503
Epoch [31/50], Train Loss: 0.1808, Val Loss: 0.2644, Val Corr X: 0.8980, Val Corr Y: 0.8449
Epoch [32/50], Train Loss: 0.1902, Val Loss: 0.2530, Val Corr X: 0.8981, Val Corr Y: 0.8490
Epoch [33/50], Train Loss: 0.1873, Val Loss: 0.2499, Val Corr X: 0.8989, Val Corr Y: 0.8501
Epoch [34/50], Train Loss: 0.1788, Val Loss: 0.2400, Val Corr X: 0.9016, Val Corr Y: 0.8544
Epoch [35/50], Train Loss: 0.1720, Val Loss: 0.2464, Val Corr X: 0.9023, Val Corr Y: 0.8529
Epoch [36/50], Train Loss: 0.1716, Val Loss: 0.2380, Val Corr X: 0.9027, Val Corr Y: 0.8577
Epoch [37/50], Train Loss: 0.1697, Val Loss: 0.2392, Val Corr X: 0.9034, Val Corr Y: 0.8547
Epoch [38/50], Train Loss: 0.1643, Val Loss: 0.2423, Val Corr X: 0.9045, Val Corr Y: 0.8541
Epoch [39/50], Train Loss: 0.1637, Val Loss: 0.2324, Val Corr X: 0.9048, Val Corr Y: 0.8578
Epoch [40/50], Train Loss: 0.1674, Val Loss: 0.2375, Val Corr X: 0.9045, Val Corr Y: 0.8554
Epoch [41/50], Train Loss: 0.1635, Val Loss: 0.2421, Val Corr X: 0.9055, Val Corr Y: 0.8550
Epoch [42/50], Train Loss: 0.1635, Val Loss: 0.2520, Val Corr X: 0.9053, Val Corr Y: 0.8530
Epoch [43/50], Train Loss: 0.1892, Val Loss: 0.2431, Val Corr X: 0.9058, Val Corr Y: 0.8540
Epoch [44/50], Train Loss: 0.1731, Val Loss: 0.2483, Val Corr X: 0.9032, Val Corr Y: 0.8578
Epoch [45/50], Train Loss: 0.1652, Val Loss: 0.2374, Val Corr X: 0.9050, Val Corr Y: 0.8587
Epoch [46/50], Train Loss: 0.1607, Val Loss: 0.2316, Val Corr X: 0.9064, Val Corr Y: 0.8597
Epoch [47/50], Train Loss: 0.1657, Val Loss: 0.2324, Val Corr X: 0.9067, Val Corr Y: 0.8600
Epoch [48/50], Train Loss: 0.1511, Val Loss: 0.2440, Val Corr X: 0.9076, Val Corr Y: 0.8561
Epoch [49/50], Train Loss: 0.1641, Val Loss: 0.2347, Val Corr X: 0.9073, Val Corr Y: 0.8569
Epoch [50/50], Train Loss: 0.1524, Val Loss: 0.2280, Val Corr X: 0.9064, Val Corr Y: 0.8633
Model saved at snn_mcmaze_split_9.pth. Exiting training loop.

--- Evaluating on Test Set for Split 9 ---
Loading model from snn_mcmaze_split_9.pth for testing...

Test Set Results (Split 9):
  Loss: 0.2285
  Correlation X: 0.9068
  Correlation Y: 0.8484
--------------------------

--- Split 10/10 ---
Calculating normalization statistics from training set...
Vel Mean (local): [55.04973   3.112976], Vel Std (local): [341.11218 291.14423]

Split 10 Data Sizes:
  Train: 65846 samples
  Validation: 14104 samples
  Test: 14145 samples

Training model for Split 10...
Using device: cuda
Epoch [1/50], Train Loss: 0.9315, Val Loss: 0.7979, Val Corr X: 0.4971, Val Corr Y: 0.5114
Epoch [2/50], Train Loss: 0.7195, Val Loss: 0.6415, Val Corr X: 0.7063, Val Corr Y: 0.6190
Epoch [3/50], Train Loss: 0.5878, Val Loss: 0.5327, Val Corr X: 0.7528, Val Corr Y: 0.6619
Epoch [4/50], Train Loss: 0.4982, Val Loss: 0.4820, Val Corr X: 0.7821, Val Corr Y: 0.6712
Epoch [5/50], Train Loss: 0.4559, Val Loss: 0.4430, Val Corr X: 0.7955, Val Corr Y: 0.7048
Epoch [6/50], Train Loss: 0.4193, Val Loss: 0.4093, Val Corr X: 0.8114, Val Corr Y: 0.7319
Epoch [7/50], Train Loss: 0.3837, Val Loss: 0.3940, Val Corr X: 0.8235, Val Corr Y: 0.7462
Epoch [8/50], Train Loss: 0.3601, Val Loss: 0.3736, Val Corr X: 0.8310, Val Corr Y: 0.7583
Epoch [9/50], Train Loss: 0.3469, Val Loss: 0.3554, Val Corr X: 0.8419, Val Corr Y: 0.7721
Epoch [10/50], Train Loss: 0.3194, Val Loss: 0.3356, Val Corr X: 0.8486, Val Corr Y: 0.7830
Epoch [11/50], Train Loss: 0.2964, Val Loss: 0.3229, Val Corr X: 0.8553, Val Corr Y: 0.7932
Epoch [12/50], Train Loss: 0.2850, Val Loss: 0.3162, Val Corr X: 0.8619, Val Corr Y: 0.8022
Epoch [13/50], Train Loss: 0.2748, Val Loss: 0.3034, Val Corr X: 0.8641, Val Corr Y: 0.8087
Epoch [14/50], Train Loss: 0.2813, Val Loss: 0.3176, Val Corr X: 0.8685, Val Corr Y: 0.8101
Epoch [15/50], Train Loss: 0.2701, Val Loss: 0.2862, Val Corr X: 0.8727, Val Corr Y: 0.8201
Epoch [16/50], Train Loss: 0.2536, Val Loss: 0.2872, Val Corr X: 0.8747, Val Corr Y: 0.8227
Epoch [17/50], Train Loss: 0.2413, Val Loss: 0.2830, Val Corr X: 0.8787, Val Corr Y: 0.8262
Epoch [18/50], Train Loss: 0.2344, Val Loss: 0.2786, Val Corr X: 0.8792, Val Corr Y: 0.8300
Epoch [19/50], Train Loss: 0.2296, Val Loss: 0.2660, Val Corr X: 0.8819, Val Corr Y: 0.8328
Epoch [20/50], Train Loss: 0.2248, Val Loss: 0.2665, Val Corr X: 0.8839, Val Corr Y: 0.8330
Epoch [21/50], Train Loss: 0.2161, Val Loss: 0.2656, Val Corr X: 0.8845, Val Corr Y: 0.8376
Epoch [22/50], Train Loss: 0.2120, Val Loss: 0.2673, Val Corr X: 0.8856, Val Corr Y: 0.8374
Epoch [23/50], Train Loss: 0.2100, Val Loss: 0.2505, Val Corr X: 0.8901, Val Corr Y: 0.8418
Epoch [24/50], Train Loss: 0.2020, Val Loss: 0.2621, Val Corr X: 0.8900, Val Corr Y: 0.8430
Epoch [25/50], Train Loss: 0.2036, Val Loss: 0.2461, Val Corr X: 0.8925, Val Corr Y: 0.8452
Epoch [26/50], Train Loss: 0.1991, Val Loss: 0.2633, Val Corr X: 0.8912, Val Corr Y: 0.8438
Epoch [27/50], Train Loss: 0.2013, Val Loss: 0.2457, Val Corr X: 0.8944, Val Corr Y: 0.8483
Epoch [28/50], Train Loss: 0.1920, Val Loss: 0.2449, Val Corr X: 0.8928, Val Corr Y: 0.8485
Epoch [29/50], Train Loss: 0.1869, Val Loss: 0.2443, Val Corr X: 0.8955, Val Corr Y: 0.8503
Epoch [30/50], Train Loss: 0.1867, Val Loss: 0.2501, Val Corr X: 0.8956, Val Corr Y: 0.8468
Epoch [31/50], Train Loss: 0.1871, Val Loss: 0.2370, Val Corr X: 0.8970, Val Corr Y: 0.8521
Epoch [32/50], Train Loss: 0.1826, Val Loss: 0.2488, Val Corr X: 0.8965, Val Corr Y: 0.8498
Epoch [33/50], Train Loss: 0.1792, Val Loss: 0.2437, Val Corr X: 0.8966, Val Corr Y: 0.8526
Epoch [34/50], Train Loss: 0.1776, Val Loss: 0.2363, Val Corr X: 0.8958, Val Corr Y: 0.8546
Epoch [35/50], Train Loss: 0.1727, Val Loss: 0.2441, Val Corr X: 0.8982, Val Corr Y: 0.8521
Epoch [36/50], Train Loss: 0.1750, Val Loss: 0.2473, Val Corr X: 0.8995, Val Corr Y: 0.8528
Epoch [37/50], Train Loss: 0.1939, Val Loss: 0.2358, Val Corr X: 0.9002, Val Corr Y: 0.8549
Epoch [38/50], Train Loss: 0.1882, Val Loss: 0.2385, Val Corr X: 0.8987, Val Corr Y: 0.8523
Epoch [39/50], Train Loss: 0.1748, Val Loss: 0.2347, Val Corr X: 0.9012, Val Corr Y: 0.8592
Epoch [40/50], Train Loss: 0.1649, Val Loss: 0.2298, Val Corr X: 0.8988, Val Corr Y: 0.8594
Epoch [41/50], Train Loss: 0.1667, Val Loss: 0.2305, Val Corr X: 0.9020, Val Corr Y: 0.8576
Epoch [42/50], Train Loss: 0.1620, Val Loss: 0.2430, Val Corr X: 0.9022, Val Corr Y: 0.8557
Epoch [43/50], Train Loss: 0.1808, Val Loss: 0.2257, Val Corr X: 0.9043, Val Corr Y: 0.8617
Epoch [44/50], Train Loss: 0.1628, Val Loss: 0.2234, Val Corr X: 0.9042, Val Corr Y: 0.8606
Epoch [45/50], Train Loss: 0.1626, Val Loss: 0.2231, Val Corr X: 0.9058, Val Corr Y: 0.8630
Epoch [46/50], Train Loss: 0.1561, Val Loss: 0.2192, Val Corr X: 0.9056, Val Corr Y: 0.8630
Epoch [47/50], Train Loss: 0.1620, Val Loss: 0.2470, Val Corr X: 0.9035, Val Corr Y: 0.8537
Epoch [48/50], Train Loss: 0.1689, Val Loss: 0.2348, Val Corr X: 0.9070, Val Corr Y: 0.8596
Epoch [49/50], Train Loss: 0.1606, Val Loss: 0.2151, Val Corr X: 0.9076, Val Corr Y: 0.8655
Epoch [50/50], Train Loss: 0.1509, Val Loss: 0.2191, Val Corr X: 0.9065, Val Corr Y: 0.8638
Model saved at snn_mcmaze_split_10.pth. Exiting training loop.

--- Evaluating on Test Set for Split 10 ---
Loading model from snn_mcmaze_split_10.pth for testing...

Test Set Results (Split 10):
  Loss: 0.2079
  Correlation X: 0.9123
  Correlation Y: 0.8657
--------------------------


===== FINAL RESULTS ACROSS ALL SPLITS =====
   split    loss  corr_x  ...  train_samples  val_samples  test_samples
0      1  0.2225  0.9128  ...          65846        14104         14145
1      2  0.2903  0.9132  ...          65846        14104         14145
2      3  0.2253  0.9085  ...          65846        14104         14145
3      4  0.2241  0.9084  ...          65846        14104         14145
4      5  0.2112  0.9153  ...          65846        14104         14145
5      6  0.2436  0.9083  ...          65846        14104         14145
6      7  0.2459  0.9020  ...          65846        14104         14145
7      8  0.2293  0.9081  ...          65846        14104         14145
8      9  0.2285  0.9068  ...          65846        14104         14145
9     10  0.2079  0.9123  ...          65846        14104         14145

[10 rows x 10 columns]

Average Performance:
  Average Test Loss: 0.2329 +/- 0.0235
  Average Test Correlation X: 0.9096 +/- 0.0039
  Average Test Correlation Y: 0.8530 +/- 0.0110
==========================================

Loading MCMaze data...
Processing MC_MAZE data from scratch...
Applying spike processing: 'count'
Spike rates shape: (94095, 182)
Hand velocity shape: (94095, 2)

VERIFICATION: Spike data shape: (94095, 182)
Data type: float32
Min value: 0.000000, Max value: 15.000000

=== SPIKE COUNTS (5x10 matrix) ===
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0

Sample values from first row: [2. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
Are these integers? True

Hand velocity shape: (94095, 2)
Trial IDs shape: (94095,)
Unique trials: 2295
Found 2295 unique trials

==================================================
Testing HEBBIAN Learning
==================================================

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 1) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.2202, Val Avg Corr: 0.0110
  >>> New best validation model saved with Avg Corr: 0.0110 <<<
Epoch [1/20], Step 1000, Train Loss: 0.9515, Val Avg Corr: 0.0398
  >>> New best validation model saved with Avg Corr: 0.0398 <<<
Epoch [1/20], Step 1500, Train Loss: 1.0779, Val Avg Corr: 0.0880
  >>> New best validation model saved with Avg Corr: 0.0880 <<<
Epoch [1/20], Step 2000, Train Loss: 1.0819, Val Avg Corr: 0.1115
  >>> New best validation model saved with Avg Corr: 0.1115 <<<
Epoch [1/20], Step 2500, Train Loss: 0.9406, Val Avg Corr: 0.1744
  >>> New best validation model saved with Avg Corr: 0.1744 <<<
Epoch [1/20], Step 3000, Train Loss: 1.0346, Val Avg Corr: 0.2183
  >>> New best validation model saved with Avg Corr: 0.2183 <<<
Epoch [1/20], Step 3500, Train Loss: 1.0459, Val Avg Corr: 0.2403
  >>> New best validation model saved with Avg Corr: 0.2403 <<<
Epoch [1/20], Step 4000, Train Loss: 0.7489, Val Avg Corr: 0.2811
  >>> New best validation model saved with Avg Corr: 0.2811 <<<
Epoch [1/20], Step 4500, Train Loss: 0.8335, Val Avg Corr: 0.2625
Epoch [1/20], Step 5000, Train Loss: 1.1704, Val Avg Corr: 0.2572
Epoch [1/20], Step 5500, Train Loss: 0.9557, Val Avg Corr: 0.3531
  >>> New best validation model saved with Avg Corr: 0.3531 <<<
Epoch [1/20], Step 6000, Train Loss: 0.9682, Val Avg Corr: 0.4139
  >>> New best validation model saved with Avg Corr: 0.4139 <<<
Epoch [1/20], Step 6500, Train Loss: 0.8049, Val Avg Corr: 0.4199
  >>> New best validation model saved with Avg Corr: 0.4199 <<<
Epoch [1/20], Step 7000, Train Loss: 0.8669, Val Avg Corr: 0.4354
  >>> New best validation model saved with Avg Corr: 0.4354 <<<
Epoch [1/20], Step 7500, Train Loss: 0.7469, Val Avg Corr: 0.4847
  >>> New best validation model saved with Avg Corr: 0.4847 <<<
Epoch [1/20], Step 8000, Train Loss: 0.7617, Val Avg Corr: 0.4860
  >>> New best validation model saved with Avg Corr: 0.4860 <<<
Epoch [1/20], Step 8500, Train Loss: 0.7598, Val Avg Corr: 0.4957
  >>> New best validation model saved with Avg Corr: 0.4957 <<<
Epoch [1/20], Step 9000, Train Loss: 0.6793, Val Avg Corr: 0.5042
  >>> New best validation model saved with Avg Corr: 0.5042 <<<
Epoch [1/20], Step 9500, Train Loss: 0.8483, Val Avg Corr: 0.5349
  >>> New best validation model saved with Avg Corr: 0.5349 <<<
Epoch [1/20], Step 10000, Train Loss: 0.8469, Val Avg Corr: 0.5412
  >>> New best validation model saved with Avg Corr: 0.5412 <<<
Epoch [1/20], Step 10500, Train Loss: 0.7343, Val Avg Corr: 0.4926
Epoch [1/20], Step 11000, Train Loss: 0.6631, Val Avg Corr: 0.4184
Epoch [1/20], Step 11500, Train Loss: 0.7565, Val Avg Corr: 0.4982
Epoch [1/20], Step 12000, Train Loss: 0.7371, Val Avg Corr: 0.4945
Epoch [1/20], Step 12500, Train Loss: 0.8952, Val Avg Corr: 0.5965
  >>> New best validation model saved with Avg Corr: 0.5965 <<<
Epoch [1/20], Step 13000, Train Loss: 0.6038, Val Avg Corr: 0.5614
Epoch [1/20], Step 13500, Train Loss: 0.6770, Val Avg Corr: 0.6154
  >>> New best validation model saved with Avg Corr: 0.6154 <<<
Epoch [1/20], Step 14000, Train Loss: 0.7160, Val Avg Corr: 0.6432
  >>> New best validation model saved with Avg Corr: 0.6432 <<<
Epoch [1/20], Step 14500, Train Loss: 0.7151, Val Avg Corr: 0.6496
  >>> New best validation model saved with Avg Corr: 0.6496 <<<
Epoch [1/20], Step 15000, Train Loss: 0.8467, Val Avg Corr: 0.6659
  >>> New best validation model saved with Avg Corr: 0.6659 <<<
Epoch [1/20], Step 15500, Train Loss: 0.5734, Val Avg Corr: 0.6871
  >>> New best validation model saved with Avg Corr: 0.6871 <<<
Epoch [1/20], Step 16000, Train Loss: 0.6119, Val Avg Corr: 0.6927
  >>> New best validation model saved with Avg Corr: 0.6927 <<<
Epoch [1/20], Step 16500, Train Loss: 0.6549, Val Avg Corr: 0.6864
Epoch [1/20], Step 17000, Train Loss: 0.4474, Val Avg Corr: 0.6968
  >>> New best validation model saved with Avg Corr: 0.6968 <<<
Epoch [1/20], Step 17500, Train Loss: 0.6984, Val Avg Corr: 0.7019
  >>> New best validation model saved with Avg Corr: 0.7019 <<<
Epoch [1/20], Step 18000, Train Loss: 0.6958, Val Avg Corr: 0.7009
Epoch [1/20], Step 18500, Train Loss: 0.6018, Val Avg Corr: 0.6952
Epoch [1/20], Step 19000, Train Loss: 0.5950, Val Avg Corr: 0.6963
Epoch [1/20], Step 19500, Train Loss: 0.5721, Val Avg Corr: 0.7291
  >>> New best validation model saved with Avg Corr: 0.7291 <<<
Epoch [1/20], Step 20000, Train Loss: 0.4985, Val Avg Corr: 0.7201
Epoch [1/20], Step 20500, Train Loss: 0.5342, Val Avg Corr: 0.7329
  >>> New best validation model saved with Avg Corr: 0.7329 <<<
Trial change detected: 677 -> 678, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.5921, Val Avg Corr: 0.7371
  >>> New best validation model saved with Avg Corr: 0.7371 <<<
Epoch [1/20], Step 21500, Train Loss: 0.4760, Val Avg Corr: 0.7335
Epoch [1/20], Step 22000, Train Loss: 0.4718, Val Avg Corr: 0.7431
  >>> New best validation model saved with Avg Corr: 0.7431 <<<
Epoch [1/20], Step 22500, Train Loss: 0.4546, Val Avg Corr: 0.7411
Epoch [1/20], Step 23000, Train Loss: 0.5307, Val Avg Corr: 0.7298
Epoch [1/20], Step 23500, Train Loss: 0.6960, Val Avg Corr: 0.7304
Epoch [1/20], Step 24000, Train Loss: 0.5601, Val Avg Corr: 0.7387
Epoch [1/20], Step 24500, Train Loss: 0.3911, Val Avg Corr: 0.7470
  >>> New best validation model saved with Avg Corr: 0.7470 <<<
Epoch [1/20], Step 25000, Train Loss: 0.4864, Val Avg Corr: 0.7529
  >>> New best validation model saved with Avg Corr: 0.7529 <<<
Epoch [1/20], Step 25500, Train Loss: 0.5289, Val Avg Corr: 0.7456
Epoch [1/20], Step 26000, Train Loss: 0.5282, Val Avg Corr: 0.7514
Epoch [1/20], Step 26500, Train Loss: 0.5992, Val Avg Corr: 0.7446
Epoch [1/20], Step 27000, Train Loss: 0.3685, Val Avg Corr: 0.7540
  >>> New best validation model saved with Avg Corr: 0.7540 <<<
Epoch [1/20], Step 27500, Train Loss: 0.4060, Val Avg Corr: 0.7552
  >>> New best validation model saved with Avg Corr: 0.7552 <<<
Epoch [1/20], Step 28000, Train Loss: 0.4751, Val Avg Corr: 0.7618
  >>> New best validation model saved with Avg Corr: 0.7618 <<<
Epoch [1/20], Step 28500, Train Loss: 0.4423, Val Avg Corr: 0.7620
  >>> New best validation model saved with Avg Corr: 0.7620 <<<
Epoch [1/20], Step 29000, Train Loss: 0.4786, Val Avg Corr: 0.7681
  >>> New best validation model saved with Avg Corr: 0.7681 <<<
Epoch [1/20], Step 29500, Train Loss: 0.4439, Val Avg Corr: 0.7724
  >>> New best validation model saved with Avg Corr: 0.7724 <<<
Epoch [1/20], Step 30000, Train Loss: 0.4473, Val Avg Corr: 0.7661
Epoch [1/20], Step 30500, Train Loss: 0.3367, Val Avg Corr: 0.7771
  >>> New best validation model saved with Avg Corr: 0.7771 <<<
Epoch [1/20], Step 31000, Train Loss: 0.5017, Val Avg Corr: 0.7808
  >>> New best validation model saved with Avg Corr: 0.7808 <<<
Epoch [1/20], Step 31500, Train Loss: 0.4338, Val Avg Corr: 0.7781
Epoch [1/20], Step 32000, Train Loss: 0.4742, Val Avg Corr: 0.7817
  >>> New best validation model saved with Avg Corr: 0.7817 <<<
Epoch [1/20], Step 32500, Train Loss: 0.3637, Val Avg Corr: 0.7753
Epoch [1/20], Step 33000, Train Loss: 0.4661, Val Avg Corr: 0.7793
Epoch [1/20], Step 33500, Train Loss: 0.4420, Val Avg Corr: 0.7713
Epoch [1/20], Step 34000, Train Loss: 0.4138, Val Avg Corr: 0.7861
  >>> New best validation model saved with Avg Corr: 0.7861 <<<
Epoch [1/20], Step 34500, Train Loss: 0.4158, Val Avg Corr: 0.7789
Epoch [1/20], Step 35000, Train Loss: 0.4419, Val Avg Corr: 0.7794
Epoch [1/20], Step 35500, Train Loss: 0.3681, Val Avg Corr: 0.7791
Epoch [1/20], Step 36000, Train Loss: 0.4101, Val Avg Corr: 0.7810
Epoch [1/20], Step 36500, Train Loss: 0.3518, Val Avg Corr: 0.7884
  >>> New best validation model saved with Avg Corr: 0.7884 <<<
Epoch [1/20], Step 37000, Train Loss: 0.4189, Val Avg Corr: 0.7858
Epoch [1/20], Step 37500, Train Loss: 0.4589, Val Avg Corr: 0.7922
  >>> New best validation model saved with Avg Corr: 0.7922 <<<
Epoch [1/20], Step 38000, Train Loss: 0.4488, Val Avg Corr: 0.7852
Epoch [1/20], Step 38500, Train Loss: 0.4588, Val Avg Corr: 0.7830
Epoch [1/20], Step 39000, Train Loss: 0.5142, Val Avg Corr: 0.7890
Epoch [1/20], Step 39500, Train Loss: 0.3726, Val Avg Corr: 0.7914
Epoch [1/20], Step 40000, Train Loss: 0.3721, Val Avg Corr: 0.7863
Epoch [1/20], Step 40500, Train Loss: 0.4501, Val Avg Corr: 0.7957
  >>> New best validation model saved with Avg Corr: 0.7957 <<<
Epoch [1/20], Step 41000, Train Loss: 0.4219, Val Avg Corr: 0.7798
Trial change detected: 1420 -> 1421, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.3159, Val Avg Corr: 0.7831
Epoch [1/20], Step 42000, Train Loss: 0.3599, Val Avg Corr: 0.7846
Epoch [1/20], Step 42500, Train Loss: 0.4406, Val Avg Corr: 0.7938
Epoch [1/20], Step 43000, Train Loss: 0.3201, Val Avg Corr: 0.7950
Epoch [1/20], Step 43500, Train Loss: 0.4816, Val Avg Corr: 0.7938
Epoch [1/20], Step 44000, Train Loss: 0.3425, Val Avg Corr: 0.7944
Epoch [1/20], Step 44500, Train Loss: 0.4945, Val Avg Corr: 0.7889
Epoch [1/20], Step 45000, Train Loss: 0.3712, Val Avg Corr: 0.7930
Epoch [1/20], Step 45500, Train Loss: 0.4222, Val Avg Corr: 0.7850
Epoch [1/20], Step 46000, Train Loss: 0.4933, Val Avg Corr: 0.7980
  >>> New best validation model saved with Avg Corr: 0.7980 <<<
Epoch [1/20], Step 46500, Train Loss: 0.3948, Val Avg Corr: 0.7894
Epoch [1/20], Step 47000, Train Loss: 0.4745, Val Avg Corr: 0.7975
Epoch [1/20], Step 47500, Train Loss: 0.3231, Val Avg Corr: 0.7917
Epoch [1/20], Step 48000, Train Loss: 0.3463, Val Avg Corr: 0.7977
Epoch [1/20], Step 48500, Train Loss: 0.3320, Val Avg Corr: 0.7938
Epoch [1/20], Step 49000, Train Loss: 0.4793, Val Avg Corr: 0.7963
Epoch [1/20], Step 49500, Train Loss: 0.4802, Val Avg Corr: 0.7991
  >>> New best validation model saved with Avg Corr: 0.7991 <<<
Epoch [1/20], Step 50000, Train Loss: 0.3057, Val Avg Corr: 0.8008
  >>> New best validation model saved with Avg Corr: 0.8008 <<<
Epoch [1/20], Step 50500, Train Loss: 0.4010, Val Avg Corr: 0.8020
  >>> New best validation model saved with Avg Corr: 0.8020 <<<
Epoch [1/20], Step 51000, Train Loss: 0.4833, Val Avg Corr: 0.8031
  >>> New best validation model saved with Avg Corr: 0.8031 <<<
Epoch [1/20], Step 51500, Train Loss: 0.3227, Val Avg Corr: 0.7957
Epoch [1/20], Step 52000, Train Loss: 0.3174, Val Avg Corr: 0.7997
Epoch [1/20], Step 52500, Train Loss: 0.3487, Val Avg Corr: 0.7998
Epoch [1/20], Step 53000, Train Loss: 0.4140, Val Avg Corr: 0.8021
Epoch [1/20], Step 53500, Train Loss: 0.4355, Val Avg Corr: 0.7913
Epoch [1/20], Step 54000, Train Loss: 0.3701, Val Avg Corr: 0.7989
Epoch [1/20], Step 54500, Train Loss: 0.3815, Val Avg Corr: 0.7979
Epoch [1/20], Step 55000, Train Loss: 0.4620, Val Avg Corr: 0.7982
Epoch [1/20], Step 55500, Train Loss: 0.4128, Val Avg Corr: 0.8051
  >>> New best validation model saved with Avg Corr: 0.8051 <<<
Epoch [1/20], Step 56000, Train Loss: 0.3411, Val Avg Corr: 0.7991
Epoch [1/20], Step 56500, Train Loss: 0.4616, Val Avg Corr: 0.8008
Epoch [1/20], Step 57000, Train Loss: 0.4364, Val Avg Corr: 0.7964
Epoch [1/20], Step 57500, Train Loss: 0.4716, Val Avg Corr: 0.8043
Epoch [1/20], Step 58000, Train Loss: 0.3888, Val Avg Corr: 0.8062
  >>> New best validation model saved with Avg Corr: 0.8062 <<<
Epoch [1/20], Step 58500, Train Loss: 0.3923, Val Avg Corr: 0.8030
Epoch [1/20], Step 59000, Train Loss: 0.3573, Val Avg Corr: 0.8069
  >>> New best validation model saved with Avg Corr: 0.8069 <<<
Epoch [1/20], Step 59500, Train Loss: 0.4115, Val Avg Corr: 0.8055
Epoch [1/20], Step 60000, Train Loss: 0.3269, Val Avg Corr: 0.8001
Epoch [1/20], Step 60500, Train Loss: 0.4321, Val Avg Corr: 0.7980
Epoch [1/20], Step 61000, Train Loss: 0.3096, Val Avg Corr: 0.8035
Epoch [1/20], Step 61500, Train Loss: 0.3310, Val Avg Corr: 0.8116
  >>> New best validation model saved with Avg Corr: 0.8116 <<<
Trial change detected: 2126 -> 2127, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3917, Val Avg Corr: 0.8059
Epoch [1/20], Step 62500, Train Loss: 0.3898, Val Avg Corr: 0.8073
Epoch [1/20], Step 63000, Train Loss: 0.3644, Val Avg Corr: 0.8159
  >>> New best validation model saved with Avg Corr: 0.8159 <<<
Epoch [1/20], Step 63500, Train Loss: 0.2997, Val Avg Corr: 0.8066
Epoch [1/20], Step 64000, Train Loss: 0.4384, Val Avg Corr: 0.8159
Epoch [1/20], Step 64500, Train Loss: 0.3733, Val Avg Corr: 0.8113
Epoch [1/20], Step 65000, Train Loss: 0.3753, Val Avg Corr: 0.8087
Epoch [1/20], Step 65500, Train Loss: 0.3619, Val Avg Corr: 0.8086
Epoch [2/20], Step 500, Train Loss: 0.4377, Val Avg Corr: 0.8111
Epoch [2/20], Step 1000, Train Loss: 0.4661, Val Avg Corr: 0.8028
Epoch [2/20], Step 1500, Train Loss: 0.4065, Val Avg Corr: 0.8161
  >>> New best validation model saved with Avg Corr: 0.8161 <<<
Epoch [2/20], Step 2000, Train Loss: 0.3300, Val Avg Corr: 0.8105
Epoch [2/20], Step 2500, Train Loss: 0.3081, Val Avg Corr: 0.8149
Epoch [2/20], Step 3000, Train Loss: 0.3255, Val Avg Corr: 0.8103
Epoch [2/20], Step 3500, Train Loss: 0.4425, Val Avg Corr: 0.8123
Epoch [2/20], Step 4000, Train Loss: 0.3073, Val Avg Corr: 0.8122
Epoch [2/20], Step 4500, Train Loss: 0.3581, Val Avg Corr: 0.8090
Epoch [2/20], Step 5000, Train Loss: 0.5323, Val Avg Corr: 0.8143
Epoch [2/20], Step 5500, Train Loss: 0.3708, Val Avg Corr: 0.8186
  >>> New best validation model saved with Avg Corr: 0.8186 <<<
Epoch [2/20], Step 6000, Train Loss: 0.3734, Val Avg Corr: 0.8078
Epoch [2/20], Step 6500, Train Loss: 0.2907, Val Avg Corr: 0.8087
Epoch [2/20], Step 7000, Train Loss: 0.3346, Val Avg Corr: 0.8162
Epoch [2/20], Step 7500, Train Loss: 0.3827, Val Avg Corr: 0.8132
Epoch [2/20], Step 8000, Train Loss: 0.3897, Val Avg Corr: 0.8008
Epoch [2/20], Step 8500, Train Loss: 0.3364, Val Avg Corr: 0.8071
Epoch [2/20], Step 9000, Train Loss: 0.4114, Val Avg Corr: 0.8148
Epoch [2/20], Step 9500, Train Loss: 0.3837, Val Avg Corr: 0.8075
Epoch [2/20], Step 10000, Train Loss: 0.3359, Val Avg Corr: 0.8140
Epoch [2/20], Step 10500, Train Loss: 0.3157, Val Avg Corr: 0.8119
Epoch [2/20], Step 11000, Train Loss: 0.3686, Val Avg Corr: 0.8058
Epoch [2/20], Step 11500, Train Loss: 0.3079, Val Avg Corr: 0.8151
Epoch [2/20], Step 12000, Train Loss: 0.3950, Val Avg Corr: 0.8075
Epoch [2/20], Step 12500, Train Loss: 0.3812, Val Avg Corr: 0.8153
Epoch [2/20], Step 13000, Train Loss: 0.2972, Val Avg Corr: 0.8028
Epoch [2/20], Step 13500, Train Loss: 0.3274, Val Avg Corr: 0.8086
Epoch [2/20], Step 14000, Train Loss: 0.3682, Val Avg Corr: 0.8153
Epoch [2/20], Step 14500, Train Loss: 0.4245, Val Avg Corr: 0.8174
Epoch [2/20], Step 15000, Train Loss: 0.4040, Val Avg Corr: 0.8134
Epoch [2/20], Step 15500, Train Loss: 0.2724, Val Avg Corr: 0.8154
Epoch [2/20], Step 16000, Train Loss: 0.3830, Val Avg Corr: 0.8083
Epoch [2/20], Step 16500, Train Loss: 0.4178, Val Avg Corr: 0.8135
Epoch [2/20], Step 17000, Train Loss: 0.2756, Val Avg Corr: 0.8167
Epoch [2/20], Step 17500, Train Loss: 0.4134, Val Avg Corr: 0.8180
Epoch [2/20], Step 18000, Train Loss: 0.3597, Val Avg Corr: 0.8196
  >>> New best validation model saved with Avg Corr: 0.8196 <<<
Epoch [2/20], Step 18500, Train Loss: 0.3720, Val Avg Corr: 0.8095
Epoch [2/20], Step 19000, Train Loss: 0.3580, Val Avg Corr: 0.8149
Epoch [2/20], Step 19500, Train Loss: 0.3835, Val Avg Corr: 0.8199
  >>> New best validation model saved with Avg Corr: 0.8199 <<<
Epoch [2/20], Step 20000, Train Loss: 0.2816, Val Avg Corr: 0.8221
  >>> New best validation model saved with Avg Corr: 0.8221 <<<
Epoch [2/20], Step 20500, Train Loss: 0.3061, Val Avg Corr: 0.8212
Trial change detected: 677 -> 678, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.3500, Val Avg Corr: 0.8217
Epoch [2/20], Step 21500, Train Loss: 0.3316, Val Avg Corr: 0.8197
Epoch [2/20], Step 22000, Train Loss: 0.3119, Val Avg Corr: 0.8182
Epoch [2/20], Step 22500, Train Loss: 0.3815, Val Avg Corr: 0.8152
Epoch [2/20], Step 23000, Train Loss: 0.3919, Val Avg Corr: 0.8177
Epoch [2/20], Step 23500, Train Loss: 0.5582, Val Avg Corr: 0.8063
Epoch [2/20], Step 24000, Train Loss: 0.4004, Val Avg Corr: 0.8120
Epoch [2/20], Step 24500, Train Loss: 0.2802, Val Avg Corr: 0.8164
Epoch [2/20], Step 25000, Train Loss: 0.3339, Val Avg Corr: 0.8212
Epoch [2/20], Step 25500, Train Loss: 0.3681, Val Avg Corr: 0.8152
Epoch [2/20], Step 26000, Train Loss: 0.3295, Val Avg Corr: 0.8163
Epoch [2/20], Step 26500, Train Loss: 0.4232, Val Avg Corr: 0.8137
Epoch [2/20], Step 27000, Train Loss: 0.2749, Val Avg Corr: 0.8061
Epoch [2/20], Step 27500, Train Loss: 0.2929, Val Avg Corr: 0.8102
Epoch [2/20], Step 28000, Train Loss: 0.4024, Val Avg Corr: 0.8158
Epoch [2/20], Step 28500, Train Loss: 0.3329, Val Avg Corr: 0.8148
Epoch [2/20], Step 29000, Train Loss: 0.3127, Val Avg Corr: 0.8148
Epoch [2/20], Step 29500, Train Loss: 0.3698, Val Avg Corr: 0.8193
Epoch [2/20], Step 30000, Train Loss: 0.3368, Val Avg Corr: 0.8160
Epoch [2/20], Step 30500, Train Loss: 0.3200, Val Avg Corr: 0.8229
  >>> New best validation model saved with Avg Corr: 0.8229 <<<
Epoch [2/20], Step 31000, Train Loss: 0.3757, Val Avg Corr: 0.8226
Epoch [2/20], Step 31500, Train Loss: 0.3458, Val Avg Corr: 0.8160
Epoch [2/20], Step 32000, Train Loss: 0.3553, Val Avg Corr: 0.8248
  >>> New best validation model saved with Avg Corr: 0.8248 <<<
Epoch [2/20], Step 32500, Train Loss: 0.2958, Val Avg Corr: 0.8184
Epoch [2/20], Step 33000, Train Loss: 0.4086, Val Avg Corr: 0.8143
Epoch [2/20], Step 33500, Train Loss: 0.3165, Val Avg Corr: 0.8127
Epoch [2/20], Step 34000, Train Loss: 0.3309, Val Avg Corr: 0.8130
Epoch [2/20], Step 34500, Train Loss: 0.3383, Val Avg Corr: 0.8139
Epoch [2/20], Step 35000, Train Loss: 0.3210, Val Avg Corr: 0.8130
Epoch [2/20], Step 35500, Train Loss: 0.2902, Val Avg Corr: 0.8213
Epoch [2/20], Step 36000, Train Loss: 0.3405, Val Avg Corr: 0.8207
Epoch [2/20], Step 36500, Train Loss: 0.2741, Val Avg Corr: 0.8224
Epoch [2/20], Step 37000, Train Loss: 0.2978, Val Avg Corr: 0.8187
Epoch [2/20], Step 37500, Train Loss: 0.3842, Val Avg Corr: 0.8207
Epoch [2/20], Step 38000, Train Loss: 0.3430, Val Avg Corr: 0.8206
Epoch [2/20], Step 38500, Train Loss: 0.3669, Val Avg Corr: 0.8177
Epoch [2/20], Step 39000, Train Loss: 0.3798, Val Avg Corr: 0.8190
Epoch [2/20], Step 39500, Train Loss: 0.3374, Val Avg Corr: 0.8177
Epoch [2/20], Step 40000, Train Loss: 0.3051, Val Avg Corr: 0.8190
Epoch [2/20], Step 40500, Train Loss: 0.3781, Val Avg Corr: 0.8200
Epoch [2/20], Step 41000, Train Loss: 0.3215, Val Avg Corr: 0.8176
Trial change detected: 1420 -> 1421, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.2695, Val Avg Corr: 0.8174
Epoch [2/20], Step 42000, Train Loss: 0.3054, Val Avg Corr: 0.8168
Epoch [2/20], Step 42500, Train Loss: 0.4171, Val Avg Corr: 0.8185
Epoch [2/20], Step 43000, Train Loss: 0.2750, Val Avg Corr: 0.8134
Epoch [2/20], Step 43500, Train Loss: 0.3897, Val Avg Corr: 0.8191
Epoch [2/20], Step 44000, Train Loss: 0.3004, Val Avg Corr: 0.8207
Epoch [2/20], Step 44500, Train Loss: 0.3996, Val Avg Corr: 0.8191
Epoch [2/20], Step 45000, Train Loss: 0.3221, Val Avg Corr: 0.8172
Epoch [2/20], Step 45500, Train Loss: 0.3510, Val Avg Corr: 0.8160
Epoch [2/20], Step 46000, Train Loss: 0.4216, Val Avg Corr: 0.8187
Epoch [2/20], Step 46500, Train Loss: 0.3416, Val Avg Corr: 0.8166
Epoch [2/20], Step 47000, Train Loss: 0.3961, Val Avg Corr: 0.8222
Epoch [2/20], Step 47500, Train Loss: 0.2672, Val Avg Corr: 0.8160
Epoch [2/20], Step 48000, Train Loss: 0.2802, Val Avg Corr: 0.8216
Epoch [2/20], Step 48500, Train Loss: 0.3227, Val Avg Corr: 0.8214
Epoch [2/20], Step 49000, Train Loss: 0.4384, Val Avg Corr: 0.8237
Epoch [2/20], Step 49500, Train Loss: 0.3990, Val Avg Corr: 0.8222
Epoch [2/20], Step 50000, Train Loss: 0.2850, Val Avg Corr: 0.8201
Epoch [2/20], Step 50500, Train Loss: 0.3496, Val Avg Corr: 0.8266
  >>> New best validation model saved with Avg Corr: 0.8266 <<<
Epoch [2/20], Step 51000, Train Loss: 0.4421, Val Avg Corr: 0.8212
Epoch [2/20], Step 51500, Train Loss: 0.2913, Val Avg Corr: 0.8230
Epoch [2/20], Step 52000, Train Loss: 0.2529, Val Avg Corr: 0.8203
Epoch [2/20], Step 52500, Train Loss: 0.2912, Val Avg Corr: 0.8195
Epoch [2/20], Step 53000, Train Loss: 0.3723, Val Avg Corr: 0.8244
Epoch [2/20], Step 53500, Train Loss: 0.3880, Val Avg Corr: 0.8173
Epoch [2/20], Step 54000, Train Loss: 0.3164, Val Avg Corr: 0.8200
Epoch [2/20], Step 54500, Train Loss: 0.3411, Val Avg Corr: 0.8215
Epoch [2/20], Step 55000, Train Loss: 0.3785, Val Avg Corr: 0.8192
Epoch [2/20], Step 55500, Train Loss: 0.3686, Val Avg Corr: 0.8166
Epoch [2/20], Step 56000, Train Loss: 0.2806, Val Avg Corr: 0.8188
Epoch [2/20], Step 56500, Train Loss: 0.3577, Val Avg Corr: 0.8162
Epoch [2/20], Step 57000, Train Loss: 0.3783, Val Avg Corr: 0.8166
Epoch [2/20], Step 57500, Train Loss: 0.3982, Val Avg Corr: 0.8243
Epoch [2/20], Step 58000, Train Loss: 0.3290, Val Avg Corr: 0.8236
Epoch [2/20], Step 58500, Train Loss: 0.3637, Val Avg Corr: 0.8259
Epoch [2/20], Step 59000, Train Loss: 0.3128, Val Avg Corr: 0.8237
Epoch [2/20], Step 59500, Train Loss: 0.3647, Val Avg Corr: 0.8282
  >>> New best validation model saved with Avg Corr: 0.8282 <<<
Epoch [2/20], Step 60000, Train Loss: 0.2805, Val Avg Corr: 0.8195
Epoch [2/20], Step 60500, Train Loss: 0.3749, Val Avg Corr: 0.8281
Epoch [2/20], Step 61000, Train Loss: 0.2707, Val Avg Corr: 0.8170
Epoch [2/20], Step 61500, Train Loss: 0.2953, Val Avg Corr: 0.8275
Trial change detected: 2126 -> 2127, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3582, Val Avg Corr: 0.8199
Epoch [2/20], Step 62500, Train Loss: 0.3368, Val Avg Corr: 0.8241
Epoch [2/20], Step 63000, Train Loss: 0.3345, Val Avg Corr: 0.8309
  >>> New best validation model saved with Avg Corr: 0.8309 <<<
Epoch [2/20], Step 63500, Train Loss: 0.2867, Val Avg Corr: 0.8306
Epoch [2/20], Step 64000, Train Loss: 0.3687, Val Avg Corr: 0.8306
Epoch [2/20], Step 64500, Train Loss: 0.3347, Val Avg Corr: 0.8206
Epoch [2/20], Step 65000, Train Loss: 0.3318, Val Avg Corr: 0.8280
Epoch [2/20], Step 65500, Train Loss: 0.3395, Val Avg Corr: 0.8284
Epoch [3/20], Step 500, Train Loss: 0.3817, Val Avg Corr: 0.8327
  >>> New best validation model saved with Avg Corr: 0.8327 <<<
Epoch [3/20], Step 1000, Train Loss: 0.4144, Val Avg Corr: 0.8267
Epoch [3/20], Step 1500, Train Loss: 0.3715, Val Avg Corr: 0.8281
Epoch [3/20], Step 2000, Train Loss: 0.2957, Val Avg Corr: 0.8239
Epoch [3/20], Step 2500, Train Loss: 0.2708, Val Avg Corr: 0.8296
Epoch [3/20], Step 3000, Train Loss: 0.2898, Val Avg Corr: 0.8301
Epoch [3/20], Step 3500, Train Loss: 0.3944, Val Avg Corr: 0.8302
Epoch [3/20], Step 4000, Train Loss: 0.2615, Val Avg Corr: 0.8302
Epoch [3/20], Step 4500, Train Loss: 0.3082, Val Avg Corr: 0.8287
Epoch [3/20], Step 5000, Train Loss: 0.4978, Val Avg Corr: 0.8315
Epoch [3/20], Step 5500, Train Loss: 0.3257, Val Avg Corr: 0.8278
Epoch [3/20], Step 6000, Train Loss: 0.3241, Val Avg Corr: 0.8232
Epoch [3/20], Step 6500, Train Loss: 0.2622, Val Avg Corr: 0.8322
Epoch [3/20], Step 7000, Train Loss: 0.2916, Val Avg Corr: 0.8249
Epoch [3/20], Step 7500, Train Loss: 0.3528, Val Avg Corr: 0.8254
Epoch [3/20], Step 8000, Train Loss: 0.3496, Val Avg Corr: 0.8247
Epoch [3/20], Step 8500, Train Loss: 0.3076, Val Avg Corr: 0.8173
Epoch [3/20], Step 9000, Train Loss: 0.3873, Val Avg Corr: 0.8299
Epoch [3/20], Step 9500, Train Loss: 0.3370, Val Avg Corr: 0.8304
Epoch [3/20], Step 10000, Train Loss: 0.3078, Val Avg Corr: 0.8273
Epoch [3/20], Step 10500, Train Loss: 0.2930, Val Avg Corr: 0.8311
Epoch [3/20], Step 11000, Train Loss: 0.3314, Val Avg Corr: 0.8236
Epoch [3/20], Step 11500, Train Loss: 0.2932, Val Avg Corr: 0.8265
Epoch [3/20], Step 12000, Train Loss: 0.3704, Val Avg Corr: 0.8266
Epoch [3/20], Step 12500, Train Loss: 0.3363, Val Avg Corr: 0.8246
Epoch [3/20], Step 13000, Train Loss: 0.2739, Val Avg Corr: 0.8263
Epoch [3/20], Step 13500, Train Loss: 0.3192, Val Avg Corr: 0.8265
Epoch [3/20], Step 14000, Train Loss: 0.3312, Val Avg Corr: 0.8274
Epoch [3/20], Step 14500, Train Loss: 0.3901, Val Avg Corr: 0.8287
Epoch [3/20], Step 15000, Train Loss: 0.3625, Val Avg Corr: 0.8333
  >>> New best validation model saved with Avg Corr: 0.8333 <<<
Epoch [3/20], Step 15500, Train Loss: 0.2623, Val Avg Corr: 0.8290
Epoch [3/20], Step 16000, Train Loss: 0.3455, Val Avg Corr: 0.8279
Epoch [3/20], Step 16500, Train Loss: 0.3799, Val Avg Corr: 0.8270
Epoch [3/20], Step 17000, Train Loss: 0.2539, Val Avg Corr: 0.8280
Epoch [3/20], Step 17500, Train Loss: 0.3807, Val Avg Corr: 0.8276
Epoch [3/20], Step 18000, Train Loss: 0.3194, Val Avg Corr: 0.8299
Epoch [3/20], Step 18500, Train Loss: 0.3348, Val Avg Corr: 0.8298
Epoch [3/20], Step 19000, Train Loss: 0.3094, Val Avg Corr: 0.8297
Epoch [3/20], Step 19500, Train Loss: 0.3610, Val Avg Corr: 0.8336
  >>> New best validation model saved with Avg Corr: 0.8336 <<<
Epoch [3/20], Step 20000, Train Loss: 0.2664, Val Avg Corr: 0.8328
Epoch [3/20], Step 20500, Train Loss: 0.2859, Val Avg Corr: 0.8303
Trial change detected: 677 -> 678, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.3206, Val Avg Corr: 0.8285
Epoch [3/20], Step 21500, Train Loss: 0.3024, Val Avg Corr: 0.8312
Epoch [3/20], Step 22000, Train Loss: 0.2866, Val Avg Corr: 0.8321
Epoch [3/20], Step 22500, Train Loss: 0.3394, Val Avg Corr: 0.8293
Epoch [3/20], Step 23000, Train Loss: 0.3482, Val Avg Corr: 0.8247
Epoch [3/20], Step 23500, Train Loss: 0.5050, Val Avg Corr: 0.8235
Epoch [3/20], Step 24000, Train Loss: 0.3586, Val Avg Corr: 0.8280
Epoch [3/20], Step 24500, Train Loss: 0.2453, Val Avg Corr: 0.8278
Epoch [3/20], Step 25000, Train Loss: 0.3030, Val Avg Corr: 0.8299
Epoch [3/20], Step 25500, Train Loss: 0.3352, Val Avg Corr: 0.8280
Epoch [3/20], Step 26000, Train Loss: 0.3029, Val Avg Corr: 0.8272
Epoch [3/20], Step 26500, Train Loss: 0.3788, Val Avg Corr: 0.8217
Epoch [3/20], Step 27000, Train Loss: 0.2575, Val Avg Corr: 0.8280
Epoch [3/20], Step 27500, Train Loss: 0.2544, Val Avg Corr: 0.8260
Epoch [3/20], Step 28000, Train Loss: 0.3664, Val Avg Corr: 0.8273
Epoch [3/20], Step 28500, Train Loss: 0.3148, Val Avg Corr: 0.8269
Epoch [3/20], Step 29000, Train Loss: 0.2892, Val Avg Corr: 0.8305
Epoch [3/20], Step 29500, Train Loss: 0.3349, Val Avg Corr: 0.8280
Epoch [3/20], Step 30000, Train Loss: 0.3116, Val Avg Corr: 0.8271
Epoch [3/20], Step 30500, Train Loss: 0.2908, Val Avg Corr: 0.8329
Epoch [3/20], Step 31000, Train Loss: 0.3544, Val Avg Corr: 0.8302
Epoch [3/20], Step 31500, Train Loss: 0.3105, Val Avg Corr: 0.8317
Epoch [3/20], Step 32000, Train Loss: 0.3298, Val Avg Corr: 0.8293
Epoch [3/20], Step 32500, Train Loss: 0.2951, Val Avg Corr: 0.8293
Epoch [3/20], Step 33000, Train Loss: 0.3793, Val Avg Corr: 0.8266
Epoch [3/20], Step 33500, Train Loss: 0.2945, Val Avg Corr: 0.8269
Epoch [3/20], Step 34000, Train Loss: 0.3187, Val Avg Corr: 0.8278
Epoch [3/20], Step 34500, Train Loss: 0.3359, Val Avg Corr: 0.8246
Epoch [3/20], Step 35000, Train Loss: 0.3005, Val Avg Corr: 0.8297
Epoch [3/20], Step 35500, Train Loss: 0.2724, Val Avg Corr: 0.8321
Epoch [3/20], Step 36000, Train Loss: 0.3268, Val Avg Corr: 0.8295
Epoch [3/20], Step 36500, Train Loss: 0.2448, Val Avg Corr: 0.8274
Epoch [3/20], Step 37000, Train Loss: 0.2560, Val Avg Corr: 0.8355
  >>> New best validation model saved with Avg Corr: 0.8355 <<<
Epoch [3/20], Step 37500, Train Loss: 0.3641, Val Avg Corr: 0.8352
Epoch [3/20], Step 38000, Train Loss: 0.3073, Val Avg Corr: 0.8356
  >>> New best validation model saved with Avg Corr: 0.8356 <<<
Epoch [3/20], Step 38500, Train Loss: 0.3443, Val Avg Corr: 0.8310
Epoch [3/20], Step 39000, Train Loss: 0.3449, Val Avg Corr: 0.8326
Epoch [3/20], Step 39500, Train Loss: 0.2933, Val Avg Corr: 0.8330
Epoch [3/20], Step 40000, Train Loss: 0.2908, Val Avg Corr: 0.8293
Epoch [3/20], Step 40500, Train Loss: 0.3466, Val Avg Corr: 0.8330
Epoch [3/20], Step 41000, Train Loss: 0.3094, Val Avg Corr: 0.8233
Trial change detected: 1420 -> 1421, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.2405, Val Avg Corr: 0.8290
Epoch [3/20], Step 42000, Train Loss: 0.2690, Val Avg Corr: 0.8329
Epoch [3/20], Step 42500, Train Loss: 0.3916, Val Avg Corr: 0.8274
Epoch [3/20], Step 43000, Train Loss: 0.2759, Val Avg Corr: 0.8260
Epoch [3/20], Step 43500, Train Loss: 0.3512, Val Avg Corr: 0.8327
Epoch [3/20], Step 44000, Train Loss: 0.2739, Val Avg Corr: 0.8332
Epoch [3/20], Step 44500, Train Loss: 0.3886, Val Avg Corr: 0.8311
Epoch [3/20], Step 45000, Train Loss: 0.2933, Val Avg Corr: 0.8286
Epoch [3/20], Step 45500, Train Loss: 0.3313, Val Avg Corr: 0.8306
Epoch [3/20], Step 46000, Train Loss: 0.3854, Val Avg Corr: 0.8297
Epoch [3/20], Step 46500, Train Loss: 0.3218, Val Avg Corr: 0.8240
Epoch [3/20], Step 47000, Train Loss: 0.3784, Val Avg Corr: 0.8326
Epoch [3/20], Step 47500, Train Loss: 0.2424, Val Avg Corr: 0.8318
Epoch [3/20], Step 48000, Train Loss: 0.2611, Val Avg Corr: 0.8238
Epoch [3/20], Step 48500, Train Loss: 0.3352, Val Avg Corr: 0.8323
Epoch [3/20], Step 49000, Train Loss: 0.4080, Val Avg Corr: 0.8294
Epoch [3/20], Step 49500, Train Loss: 0.3826, Val Avg Corr: 0.8249
Epoch [3/20], Step 50000, Train Loss: 0.2670, Val Avg Corr: 0.8225
Epoch [3/20], Step 50500, Train Loss: 0.3487, Val Avg Corr: 0.8324
Epoch [3/20], Step 51000, Train Loss: 0.4200, Val Avg Corr: 0.8312
Epoch [3/20], Step 51500, Train Loss: 0.2753, Val Avg Corr: 0.8307
Epoch [3/20], Step 52000, Train Loss: 0.2469, Val Avg Corr: 0.8296
Epoch [3/20], Step 52500, Train Loss: 0.2974, Val Avg Corr: 0.8304
Epoch [3/20], Step 53000, Train Loss: 0.3314, Val Avg Corr: 0.8323
Epoch [3/20], Step 53500, Train Loss: 0.3403, Val Avg Corr: 0.8268
Epoch [3/20], Step 54000, Train Loss: 0.2943, Val Avg Corr: 0.8287
Epoch [3/20], Step 54500, Train Loss: 0.3164, Val Avg Corr: 0.8285
Epoch [3/20], Step 55000, Train Loss: 0.3800, Val Avg Corr: 0.8262
Epoch [3/20], Step 55500, Train Loss: 0.3477, Val Avg Corr: 0.8299
Epoch [3/20], Step 56000, Train Loss: 0.2586, Val Avg Corr: 0.8293
Epoch [3/20], Step 56500, Train Loss: 0.3518, Val Avg Corr: 0.8262
Epoch [3/20], Step 57000, Train Loss: 0.3433, Val Avg Corr: 0.8313
Epoch [3/20], Step 57500, Train Loss: 0.3724, Val Avg Corr: 0.8318
Epoch [3/20], Step 58000, Train Loss: 0.3085, Val Avg Corr: 0.8328
Epoch [3/20], Step 58500, Train Loss: 0.3314, Val Avg Corr: 0.8333
Epoch [3/20], Step 59000, Train Loss: 0.2888, Val Avg Corr: 0.8278
Epoch [3/20], Step 59500, Train Loss: 0.3678, Val Avg Corr: 0.8320
Epoch [3/20], Step 60000, Train Loss: 0.2973, Val Avg Corr: 0.8336
Epoch [3/20], Step 60500, Train Loss: 0.3327, Val Avg Corr: 0.8316
Epoch [3/20], Step 61000, Train Loss: 0.2475, Val Avg Corr: 0.8251
Epoch [3/20], Step 61500, Train Loss: 0.2684, Val Avg Corr: 0.8377
  >>> New best validation model saved with Avg Corr: 0.8377 <<<
Trial change detected: 2126 -> 2127, resetting states
Epoch [3/20], Step 62000, Train Loss: 0.3348, Val Avg Corr: 0.8321
Epoch [3/20], Step 62500, Train Loss: 0.3188, Val Avg Corr: 0.8369
Epoch [3/20], Step 63000, Train Loss: 0.3062, Val Avg Corr: 0.8408
  >>> New best validation model saved with Avg Corr: 0.8408 <<<
Epoch [3/20], Step 63500, Train Loss: 0.2587, Val Avg Corr: 0.8430
  >>> New best validation model saved with Avg Corr: 0.8430 <<<
Epoch [3/20], Step 64000, Train Loss: 0.3406, Val Avg Corr: 0.8383
Epoch [3/20], Step 64500, Train Loss: 0.3103, Val Avg Corr: 0.8341
Epoch [3/20], Step 65000, Train Loss: 0.3191, Val Avg Corr: 0.8381
Epoch [3/20], Step 65500, Train Loss: 0.3253, Val Avg Corr: 0.8393
Epoch [4/20], Step 500, Train Loss: 0.3539, Val Avg Corr: 0.8399
Epoch [4/20], Step 1000, Train Loss: 0.4080, Val Avg Corr: 0.8413
Epoch [4/20], Step 1500, Train Loss: 0.3446, Val Avg Corr: 0.8430
  >>> New best validation model saved with Avg Corr: 0.8430 <<<
Epoch [4/20], Step 2000, Train Loss: 0.2837, Val Avg Corr: 0.8256
Epoch [4/20], Step 2500, Train Loss: 0.2573, Val Avg Corr: 0.8313
Epoch [4/20], Step 3000, Train Loss: 0.2821, Val Avg Corr: 0.8364
Epoch [4/20], Step 3500, Train Loss: 0.3697, Val Avg Corr: 0.8337
Epoch [4/20], Step 4000, Train Loss: 0.2442, Val Avg Corr: 0.8373
Epoch [4/20], Step 4500, Train Loss: 0.2969, Val Avg Corr: 0.8364
Epoch [4/20], Step 5000, Train Loss: 0.4807, Val Avg Corr: 0.8391
Epoch [4/20], Step 5500, Train Loss: 0.3043, Val Avg Corr: 0.8400
Epoch [4/20], Step 6000, Train Loss: 0.3083, Val Avg Corr: 0.8372
Epoch [4/20], Step 6500, Train Loss: 0.2566, Val Avg Corr: 0.8355
Epoch [4/20], Step 7000, Train Loss: 0.2772, Val Avg Corr: 0.8351
Epoch [4/20], Step 7500, Train Loss: 0.3499, Val Avg Corr: 0.8381
Epoch [4/20], Step 8000, Train Loss: 0.3418, Val Avg Corr: 0.8280
Epoch [4/20], Step 8500, Train Loss: 0.2873, Val Avg Corr: 0.8281
Epoch [4/20], Step 9000, Train Loss: 0.3619, Val Avg Corr: 0.8298
Epoch [4/20], Step 9500, Train Loss: 0.3305, Val Avg Corr: 0.8340
Epoch [4/20], Step 10000, Train Loss: 0.2894, Val Avg Corr: 0.8362
Epoch [4/20], Step 10500, Train Loss: 0.2850, Val Avg Corr: 0.8354
Epoch [4/20], Step 11000, Train Loss: 0.3040, Val Avg Corr: 0.8218
Epoch [4/20], Step 11500, Train Loss: 0.2656, Val Avg Corr: 0.8368
Epoch [4/20], Step 12000, Train Loss: 0.3406, Val Avg Corr: 0.8281
Epoch [4/20], Step 12500, Train Loss: 0.3096, Val Avg Corr: 0.8371
Epoch [4/20], Step 13000, Train Loss: 0.2596, Val Avg Corr: 0.8367
Epoch [4/20], Step 13500, Train Loss: 0.2936, Val Avg Corr: 0.8369
Epoch [4/20], Step 14000, Train Loss: 0.3219, Val Avg Corr: 0.8347
Epoch [4/20], Step 14500, Train Loss: 0.3684, Val Avg Corr: 0.8369
Epoch [4/20], Step 15000, Train Loss: 0.3276, Val Avg Corr: 0.8353
Epoch [4/20], Step 15500, Train Loss: 0.2498, Val Avg Corr: 0.8364
Epoch [4/20], Step 16000, Train Loss: 0.3192, Val Avg Corr: 0.8342
Epoch [4/20], Step 16500, Train Loss: 0.3460, Val Avg Corr: 0.8363
Epoch [4/20], Step 17000, Train Loss: 0.2330, Val Avg Corr: 0.8350
Epoch [4/20], Step 17500, Train Loss: 0.3599, Val Avg Corr: 0.8366
Epoch [4/20], Step 18000, Train Loss: 0.3026, Val Avg Corr: 0.8433
  >>> New best validation model saved with Avg Corr: 0.8433 <<<
Epoch [4/20], Step 18500, Train Loss: 0.3059, Val Avg Corr: 0.8429
Epoch [4/20], Step 19000, Train Loss: 0.2901, Val Avg Corr: 0.8331
Epoch [4/20], Step 19500, Train Loss: 0.3547, Val Avg Corr: 0.8415
Epoch [4/20], Step 20000, Train Loss: 0.2570, Val Avg Corr: 0.8425
Epoch [4/20], Step 20500, Train Loss: 0.2724, Val Avg Corr: 0.8396
Trial change detected: 677 -> 678, resetting states
Epoch [4/20], Step 21000, Train Loss: 0.3106, Val Avg Corr: 0.8427
Epoch [4/20], Step 21500, Train Loss: 0.2934, Val Avg Corr: 0.8381
Epoch [4/20], Step 22000, Train Loss: 0.2544, Val Avg Corr: 0.8424
Epoch [4/20], Step 22500, Train Loss: 0.3209, Val Avg Corr: 0.8350
Epoch [4/20], Step 23000, Train Loss: 0.3204, Val Avg Corr: 0.8392
Epoch [4/20], Step 23500, Train Loss: 0.4651, Val Avg Corr: 0.8281
Epoch [4/20], Step 24000, Train Loss: 0.3374, Val Avg Corr: 0.8310
Epoch [4/20], Step 24500, Train Loss: 0.2365, Val Avg Corr: 0.8305
Epoch [4/20], Step 25000, Train Loss: 0.2914, Val Avg Corr: 0.8359
Epoch [4/20], Step 25500, Train Loss: 0.3083, Val Avg Corr: 0.8346
Epoch [4/20], Step 26000, Train Loss: 0.2945, Val Avg Corr: 0.8315
Epoch [4/20], Step 26500, Train Loss: 0.3526, Val Avg Corr: 0.8274
Epoch [4/20], Step 27000, Train Loss: 0.2296, Val Avg Corr: 0.8340
Epoch [4/20], Step 27500, Train Loss: 0.2404, Val Avg Corr: 0.8353
Epoch [4/20], Step 28000, Train Loss: 0.3562, Val Avg Corr: 0.8331
Epoch [4/20], Step 28500, Train Loss: 0.2886, Val Avg Corr: 0.8400
Epoch [4/20], Step 29000, Train Loss: 0.2692, Val Avg Corr: 0.8355
Epoch [4/20], Step 29500, Train Loss: 0.3267, Val Avg Corr: 0.8335
Epoch [4/20], Step 30000, Train Loss: 0.3055, Val Avg Corr: 0.8356
Epoch [4/20], Step 30500, Train Loss: 0.2742, Val Avg Corr: 0.8392
Epoch [4/20], Step 31000, Train Loss: 0.3302, Val Avg Corr: 0.8369
Epoch [4/20], Step 31500, Train Loss: 0.2984, Val Avg Corr: 0.8373
Epoch [4/20], Step 32000, Train Loss: 0.3185, Val Avg Corr: 0.8386
Epoch [4/20], Step 32500, Train Loss: 0.2586, Val Avg Corr: 0.8329
Epoch [4/20], Step 33000, Train Loss: 0.3493, Val Avg Corr: 0.8372
Epoch [4/20], Step 33500, Train Loss: 0.2763, Val Avg Corr: 0.8289
Epoch [4/20], Step 34000, Train Loss: 0.3012, Val Avg Corr: 0.8348
Epoch [4/20], Step 34500, Train Loss: 0.3144, Val Avg Corr: 0.8321
Epoch [4/20], Step 35000, Train Loss: 0.2759, Val Avg Corr: 0.8345
Epoch [4/20], Step 35500, Train Loss: 0.2465, Val Avg Corr: 0.8365
Epoch [4/20], Step 36000, Train Loss: 0.3178, Val Avg Corr: 0.8422
Epoch [4/20], Step 36500, Train Loss: 0.2360, Val Avg Corr: 0.8377
Epoch [4/20], Step 37000, Train Loss: 0.2315, Val Avg Corr: 0.8385
Epoch [4/20], Step 37500, Train Loss: 0.3563, Val Avg Corr: 0.8421
Epoch [4/20], Step 38000, Train Loss: 0.2989, Val Avg Corr: 0.8420
Epoch [4/20], Step 38500, Train Loss: 0.3381, Val Avg Corr: 0.8363
Epoch [4/20], Step 39000, Train Loss: 0.3312, Val Avg Corr: 0.8382
Epoch [4/20], Step 39500, Train Loss: 0.2942, Val Avg Corr: 0.8425
Epoch [4/20], Step 40000, Train Loss: 0.2748, Val Avg Corr: 0.8342
Epoch [4/20], Step 40500, Train Loss: 0.3223, Val Avg Corr: 0.8346
Epoch [4/20], Step 41000, Train Loss: 0.2936, Val Avg Corr: 0.8319
Trial change detected: 1420 -> 1421, resetting states
Epoch [4/20], Step 41500, Train Loss: 0.2346, Val Avg Corr: 0.8371
Epoch [4/20], Step 42000, Train Loss: 0.2486, Val Avg Corr: 0.8377
Epoch [4/20], Step 42500, Train Loss: 0.3743, Val Avg Corr: 0.8421
Epoch [4/20], Step 43000, Train Loss: 0.2521, Val Avg Corr: 0.8410
Early stopping triggered after 43000 steps in epoch 4.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8433
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8285, Y=0.7967, Avg=0.8126

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 2) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.3460, Val Avg Corr: -0.0180
  >>> New best validation model saved with Avg Corr: -0.0180 <<<
Epoch [1/20], Step 1000, Train Loss: 1.1896, Val Avg Corr: 0.0052
  >>> New best validation model saved with Avg Corr: 0.0052 <<<
Epoch [1/20], Step 1500, Train Loss: 0.8606, Val Avg Corr: 0.0079
  >>> New best validation model saved with Avg Corr: 0.0079 <<<
Epoch [1/20], Step 2000, Train Loss: 0.9870, Val Avg Corr: 0.0343
  >>> New best validation model saved with Avg Corr: 0.0343 <<<
Epoch [1/20], Step 2500, Train Loss: 0.9882, Val Avg Corr: 0.0908
  >>> New best validation model saved with Avg Corr: 0.0908 <<<
Epoch [1/20], Step 3000, Train Loss: 0.9679, Val Avg Corr: 0.1483
  >>> New best validation model saved with Avg Corr: 0.1483 <<<
Epoch [1/20], Step 3500, Train Loss: 0.8061, Val Avg Corr: 0.1699
  >>> New best validation model saved with Avg Corr: 0.1699 <<<
Epoch [1/20], Step 4000, Train Loss: 1.0849, Val Avg Corr: 0.1660
Epoch [1/20], Step 4500, Train Loss: 1.0122, Val Avg Corr: 0.1924
  >>> New best validation model saved with Avg Corr: 0.1924 <<<
Epoch [1/20], Step 5000, Train Loss: 0.9479, Val Avg Corr: 0.2105
  >>> New best validation model saved with Avg Corr: 0.2105 <<<
Epoch [1/20], Step 5500, Train Loss: 0.7664, Val Avg Corr: 0.2266
  >>> New best validation model saved with Avg Corr: 0.2266 <<<
Epoch [1/20], Step 6000, Train Loss: 0.9279, Val Avg Corr: 0.2668
  >>> New best validation model saved with Avg Corr: 0.2668 <<<
Epoch [1/20], Step 6500, Train Loss: 0.8684, Val Avg Corr: 0.2758
  >>> New best validation model saved with Avg Corr: 0.2758 <<<
Epoch [1/20], Step 7000, Train Loss: 0.8100, Val Avg Corr: 0.3160
  >>> New best validation model saved with Avg Corr: 0.3160 <<<
Epoch [1/20], Step 7500, Train Loss: 0.8864, Val Avg Corr: 0.3481
  >>> New best validation model saved with Avg Corr: 0.3481 <<<
Epoch [1/20], Step 8000, Train Loss: 0.7120, Val Avg Corr: 0.3895
  >>> New best validation model saved with Avg Corr: 0.3895 <<<
Epoch [1/20], Step 8500, Train Loss: 0.8215, Val Avg Corr: 0.4176
  >>> New best validation model saved with Avg Corr: 0.4176 <<<
Epoch [1/20], Step 9000, Train Loss: 0.8345, Val Avg Corr: 0.3790
Epoch [1/20], Step 9500, Train Loss: 0.7519, Val Avg Corr: 0.3555
Epoch [1/20], Step 10000, Train Loss: 0.7856, Val Avg Corr: 0.3551
Epoch [1/20], Step 10500, Train Loss: 1.0642, Val Avg Corr: 0.4050
Epoch [1/20], Step 11000, Train Loss: 0.7856, Val Avg Corr: 0.4050
Epoch [1/20], Step 11500, Train Loss: 0.8379, Val Avg Corr: 0.4818
  >>> New best validation model saved with Avg Corr: 0.4818 <<<
Epoch [1/20], Step 12000, Train Loss: 0.8635, Val Avg Corr: 0.5091
  >>> New best validation model saved with Avg Corr: 0.5091 <<<
Epoch [1/20], Step 12500, Train Loss: 0.8400, Val Avg Corr: 0.5156
  >>> New best validation model saved with Avg Corr: 0.5156 <<<
Epoch [1/20], Step 13000, Train Loss: 0.8168, Val Avg Corr: 0.5165
  >>> New best validation model saved with Avg Corr: 0.5165 <<<
Epoch [1/20], Step 13500, Train Loss: 0.6360, Val Avg Corr: 0.5353
  >>> New best validation model saved with Avg Corr: 0.5353 <<<
Epoch [1/20], Step 14000, Train Loss: 0.9047, Val Avg Corr: 0.5434
  >>> New best validation model saved with Avg Corr: 0.5434 <<<
Epoch [1/20], Step 14500, Train Loss: 0.7116, Val Avg Corr: 0.5400
Epoch [1/20], Step 15000, Train Loss: 0.5858, Val Avg Corr: 0.5694
  >>> New best validation model saved with Avg Corr: 0.5694 <<<
Epoch [1/20], Step 15500, Train Loss: 0.8897, Val Avg Corr: 0.5781
  >>> New best validation model saved with Avg Corr: 0.5781 <<<
Epoch [1/20], Step 16000, Train Loss: 0.7606, Val Avg Corr: 0.5617
Epoch [1/20], Step 16500, Train Loss: 0.6070, Val Avg Corr: 0.5661
Epoch [1/20], Step 17000, Train Loss: 1.0160, Val Avg Corr: 0.5786
  >>> New best validation model saved with Avg Corr: 0.5786 <<<
Epoch [1/20], Step 17500, Train Loss: 0.5927, Val Avg Corr: 0.6270
  >>> New best validation model saved with Avg Corr: 0.6270 <<<
Epoch [1/20], Step 18000, Train Loss: 0.5833, Val Avg Corr: 0.6185
Epoch [1/20], Step 18500, Train Loss: 0.5787, Val Avg Corr: 0.6186
Epoch [1/20], Step 19000, Train Loss: 0.7062, Val Avg Corr: 0.6382
  >>> New best validation model saved with Avg Corr: 0.6382 <<<
Epoch [1/20], Step 19500, Train Loss: 0.4625, Val Avg Corr: 0.6544
  >>> New best validation model saved with Avg Corr: 0.6544 <<<
Epoch [1/20], Step 20000, Train Loss: 0.4515, Val Avg Corr: 0.6586
  >>> New best validation model saved with Avg Corr: 0.6586 <<<
Epoch [1/20], Step 20500, Train Loss: 0.6001, Val Avg Corr: 0.6509
Trial change detected: 763 -> 764, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.6554, Val Avg Corr: 0.6472
Epoch [1/20], Step 21500, Train Loss: 0.7828, Val Avg Corr: 0.6507
Epoch [1/20], Step 22000, Train Loss: 0.5626, Val Avg Corr: 0.6616
  >>> New best validation model saved with Avg Corr: 0.6616 <<<
Epoch [1/20], Step 22500, Train Loss: 0.4445, Val Avg Corr: 0.6607
Epoch [1/20], Step 23000, Train Loss: 0.6127, Val Avg Corr: 0.6910
  >>> New best validation model saved with Avg Corr: 0.6910 <<<
Epoch [1/20], Step 23500, Train Loss: 0.6673, Val Avg Corr: 0.6892
Epoch [1/20], Step 24000, Train Loss: 0.6548, Val Avg Corr: 0.6967
  >>> New best validation model saved with Avg Corr: 0.6967 <<<
Epoch [1/20], Step 24500, Train Loss: 0.5981, Val Avg Corr: 0.6961
Epoch [1/20], Step 25000, Train Loss: 0.4024, Val Avg Corr: 0.7037
  >>> New best validation model saved with Avg Corr: 0.7037 <<<
Epoch [1/20], Step 25500, Train Loss: 0.4690, Val Avg Corr: 0.7002
Epoch [1/20], Step 26000, Train Loss: 0.5079, Val Avg Corr: 0.7116
  >>> New best validation model saved with Avg Corr: 0.7116 <<<
Epoch [1/20], Step 26500, Train Loss: 0.4176, Val Avg Corr: 0.7042
Epoch [1/20], Step 27000, Train Loss: 0.5388, Val Avg Corr: 0.7098
Epoch [1/20], Step 27500, Train Loss: 0.5438, Val Avg Corr: 0.7143
  >>> New best validation model saved with Avg Corr: 0.7143 <<<
Epoch [1/20], Step 28000, Train Loss: 0.4434, Val Avg Corr: 0.7128
Epoch [1/20], Step 28500, Train Loss: 0.3567, Val Avg Corr: 0.7184
  >>> New best validation model saved with Avg Corr: 0.7184 <<<
Epoch [1/20], Step 29000, Train Loss: 0.4301, Val Avg Corr: 0.7224
  >>> New best validation model saved with Avg Corr: 0.7224 <<<
Epoch [1/20], Step 29500, Train Loss: 0.5375, Val Avg Corr: 0.7260
  >>> New best validation model saved with Avg Corr: 0.7260 <<<
Epoch [1/20], Step 30000, Train Loss: 0.5458, Val Avg Corr: 0.7157
Epoch [1/20], Step 30500, Train Loss: 0.4306, Val Avg Corr: 0.7336
  >>> New best validation model saved with Avg Corr: 0.7336 <<<
Epoch [1/20], Step 31000, Train Loss: 0.5399, Val Avg Corr: 0.7324
Epoch [1/20], Step 31500, Train Loss: 0.5286, Val Avg Corr: 0.7248
Epoch [1/20], Step 32000, Train Loss: 0.3971, Val Avg Corr: 0.7312
Epoch [1/20], Step 32500, Train Loss: 0.4372, Val Avg Corr: 0.7286
Epoch [1/20], Step 33000, Train Loss: 0.5745, Val Avg Corr: 0.7293
Epoch [1/20], Step 33500, Train Loss: 0.4257, Val Avg Corr: 0.7288
Epoch [1/20], Step 34000, Train Loss: 0.3594, Val Avg Corr: 0.7292
Epoch [1/20], Step 34500, Train Loss: 0.3674, Val Avg Corr: 0.7380
  >>> New best validation model saved with Avg Corr: 0.7380 <<<
Epoch [1/20], Step 35000, Train Loss: 0.4435, Val Avg Corr: 0.7370
Epoch [1/20], Step 35500, Train Loss: 0.4062, Val Avg Corr: 0.7359
Epoch [1/20], Step 36000, Train Loss: 0.3932, Val Avg Corr: 0.7308
Epoch [1/20], Step 36500, Train Loss: 0.5443, Val Avg Corr: 0.7397
  >>> New best validation model saved with Avg Corr: 0.7397 <<<
Epoch [1/20], Step 37000, Train Loss: 0.5094, Val Avg Corr: 0.7377
Epoch [1/20], Step 37500, Train Loss: 0.4699, Val Avg Corr: 0.7441
  >>> New best validation model saved with Avg Corr: 0.7441 <<<
Epoch [1/20], Step 38000, Train Loss: 0.5192, Val Avg Corr: 0.7378
Epoch [1/20], Step 38500, Train Loss: 0.3806, Val Avg Corr: 0.7470
  >>> New best validation model saved with Avg Corr: 0.7470 <<<
Epoch [1/20], Step 39000, Train Loss: 0.3980, Val Avg Corr: 0.7430
Epoch [1/20], Step 39500, Train Loss: 0.4721, Val Avg Corr: 0.7390
Epoch [1/20], Step 40000, Train Loss: 0.3624, Val Avg Corr: 0.7415
Epoch [1/20], Step 40500, Train Loss: 0.3220, Val Avg Corr: 0.7386
Epoch [1/20], Step 41000, Train Loss: 0.3909, Val Avg Corr: 0.7384
Trial change detected: 1451 -> 1452, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.4432, Val Avg Corr: 0.7523
  >>> New best validation model saved with Avg Corr: 0.7523 <<<
Epoch [1/20], Step 42000, Train Loss: 0.4108, Val Avg Corr: 0.7403
Epoch [1/20], Step 42500, Train Loss: 0.5231, Val Avg Corr: 0.7424
Epoch [1/20], Step 43000, Train Loss: 0.3859, Val Avg Corr: 0.7439
Epoch [1/20], Step 43500, Train Loss: 0.4825, Val Avg Corr: 0.7415
Epoch [1/20], Step 44000, Train Loss: 0.4518, Val Avg Corr: 0.7456
Epoch [1/20], Step 44500, Train Loss: 0.3990, Val Avg Corr: 0.7468
Epoch [1/20], Step 45000, Train Loss: 0.3583, Val Avg Corr: 0.7512
Epoch [1/20], Step 45500, Train Loss: 0.4864, Val Avg Corr: 0.7504
Epoch [1/20], Step 46000, Train Loss: 0.3926, Val Avg Corr: 0.7522
Epoch [1/20], Step 46500, Train Loss: 0.4336, Val Avg Corr: 0.7484
Epoch [1/20], Step 47000, Train Loss: 0.3843, Val Avg Corr: 0.7503
Epoch [1/20], Step 47500, Train Loss: 0.3201, Val Avg Corr: 0.7453
Epoch [1/20], Step 48000, Train Loss: 0.3820, Val Avg Corr: 0.7446
Epoch [1/20], Step 48500, Train Loss: 0.3353, Val Avg Corr: 0.7518
Epoch [1/20], Step 49000, Train Loss: 0.4798, Val Avg Corr: 0.7568
  >>> New best validation model saved with Avg Corr: 0.7568 <<<
Epoch [1/20], Step 49500, Train Loss: 0.4897, Val Avg Corr: 0.7659
  >>> New best validation model saved with Avg Corr: 0.7659 <<<
Epoch [1/20], Step 50000, Train Loss: 0.3820, Val Avg Corr: 0.7445
Epoch [1/20], Step 50500, Train Loss: 0.3947, Val Avg Corr: 0.7584
Epoch [1/20], Step 51000, Train Loss: 0.4034, Val Avg Corr: 0.7592
Epoch [1/20], Step 51500, Train Loss: 0.3588, Val Avg Corr: 0.7560
Epoch [1/20], Step 52000, Train Loss: 0.3162, Val Avg Corr: 0.7599
Epoch [1/20], Step 52500, Train Loss: 0.4818, Val Avg Corr: 0.7499
Epoch [1/20], Step 53000, Train Loss: 0.4479, Val Avg Corr: 0.7620
Epoch [1/20], Step 53500, Train Loss: 0.4956, Val Avg Corr: 0.7626
Epoch [1/20], Step 54000, Train Loss: 0.3714, Val Avg Corr: 0.7531
Epoch [1/20], Step 54500, Train Loss: 0.4679, Val Avg Corr: 0.7613
Epoch [1/20], Step 55000, Train Loss: 0.5806, Val Avg Corr: 0.7601
Epoch [1/20], Step 55500, Train Loss: 0.4367, Val Avg Corr: 0.7594
Epoch [1/20], Step 56000, Train Loss: 0.3593, Val Avg Corr: 0.7628
Epoch [1/20], Step 56500, Train Loss: 0.4844, Val Avg Corr: 0.7600
Epoch [1/20], Step 57000, Train Loss: 0.3453, Val Avg Corr: 0.7607
Epoch [1/20], Step 57500, Train Loss: 0.3620, Val Avg Corr: 0.7670
  >>> New best validation model saved with Avg Corr: 0.7670 <<<
Epoch [1/20], Step 58000, Train Loss: 0.3533, Val Avg Corr: 0.7694
  >>> New best validation model saved with Avg Corr: 0.7694 <<<
Epoch [1/20], Step 58500, Train Loss: 0.3977, Val Avg Corr: 0.7660
Epoch [1/20], Step 59000, Train Loss: 0.4022, Val Avg Corr: 0.7668
Epoch [1/20], Step 59500, Train Loss: 0.3460, Val Avg Corr: 0.7551
Epoch [1/20], Step 60000, Train Loss: 0.2774, Val Avg Corr: 0.7673
Epoch [1/20], Step 60500, Train Loss: 0.4521, Val Avg Corr: 0.7618
Epoch [1/20], Step 61000, Train Loss: 0.3667, Val Avg Corr: 0.7641
Epoch [1/20], Step 61500, Train Loss: 0.4213, Val Avg Corr: 0.7766
  >>> New best validation model saved with Avg Corr: 0.7766 <<<
Trial change detected: 2139 -> 2141, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3995, Val Avg Corr: 0.7734
Epoch [1/20], Step 62500, Train Loss: 0.3830, Val Avg Corr: 0.7756
Epoch [1/20], Step 63000, Train Loss: 0.3090, Val Avg Corr: 0.7706
Epoch [1/20], Step 63500, Train Loss: 0.3971, Val Avg Corr: 0.7760
Epoch [1/20], Step 64000, Train Loss: 0.3887, Val Avg Corr: 0.7732
Epoch [1/20], Step 64500, Train Loss: 0.4097, Val Avg Corr: 0.7733
Epoch [1/20], Step 65000, Train Loss: 0.3133, Val Avg Corr: 0.7727
Epoch [1/20], Step 65500, Train Loss: 0.4013, Val Avg Corr: 0.7735
Epoch [2/20], Step 500, Train Loss: 0.5091, Val Avg Corr: 0.7759
Epoch [2/20], Step 1000, Train Loss: 0.5939, Val Avg Corr: 0.7751
Epoch [2/20], Step 1500, Train Loss: 0.3725, Val Avg Corr: 0.7738
Epoch [2/20], Step 2000, Train Loss: 0.2961, Val Avg Corr: 0.7778
  >>> New best validation model saved with Avg Corr: 0.7778 <<<
Epoch [2/20], Step 2500, Train Loss: 0.3638, Val Avg Corr: 0.7779
  >>> New best validation model saved with Avg Corr: 0.7779 <<<
Epoch [2/20], Step 3000, Train Loss: 0.3944, Val Avg Corr: 0.7743
Epoch [2/20], Step 3500, Train Loss: 0.2822, Val Avg Corr: 0.7771
Epoch [2/20], Step 4000, Train Loss: 0.4737, Val Avg Corr: 0.7821
  >>> New best validation model saved with Avg Corr: 0.7821 <<<
Epoch [2/20], Step 4500, Train Loss: 0.4254, Val Avg Corr: 0.7758
Epoch [2/20], Step 5000, Train Loss: 0.3778, Val Avg Corr: 0.7707
Epoch [2/20], Step 5500, Train Loss: 0.2626, Val Avg Corr: 0.7772
Epoch [2/20], Step 6000, Train Loss: 0.3585, Val Avg Corr: 0.7709
Epoch [2/20], Step 6500, Train Loss: 0.4225, Val Avg Corr: 0.7775
Epoch [2/20], Step 7000, Train Loss: 0.3567, Val Avg Corr: 0.7712
Epoch [2/20], Step 7500, Train Loss: 0.4374, Val Avg Corr: 0.7801
Epoch [2/20], Step 8000, Train Loss: 0.3232, Val Avg Corr: 0.7738
Epoch [2/20], Step 8500, Train Loss: 0.2931, Val Avg Corr: 0.7732
Epoch [2/20], Step 9000, Train Loss: 0.3508, Val Avg Corr: 0.7772
Epoch [2/20], Step 9500, Train Loss: 0.3578, Val Avg Corr: 0.7721
Epoch [2/20], Step 10000, Train Loss: 0.3987, Val Avg Corr: 0.7648
Epoch [2/20], Step 10500, Train Loss: 0.4016, Val Avg Corr: 0.7699
Epoch [2/20], Step 11000, Train Loss: 0.3691, Val Avg Corr: 0.7735
Epoch [2/20], Step 11500, Train Loss: 0.3811, Val Avg Corr: 0.7808
Epoch [2/20], Step 12000, Train Loss: 0.4253, Val Avg Corr: 0.7733
Epoch [2/20], Step 12500, Train Loss: 0.3270, Val Avg Corr: 0.7781
Epoch [2/20], Step 13000, Train Loss: 0.3884, Val Avg Corr: 0.7709
Epoch [2/20], Step 13500, Train Loss: 0.2970, Val Avg Corr: 0.7752
Epoch [2/20], Step 14000, Train Loss: 0.3933, Val Avg Corr: 0.7717
Epoch [2/20], Step 14500, Train Loss: 0.3504, Val Avg Corr: 0.7808
Epoch [2/20], Step 15000, Train Loss: 0.2910, Val Avg Corr: 0.7733
Epoch [2/20], Step 15500, Train Loss: 0.4647, Val Avg Corr: 0.7724
Epoch [2/20], Step 16000, Train Loss: 0.3686, Val Avg Corr: 0.7829
  >>> New best validation model saved with Avg Corr: 0.7829 <<<
Epoch [2/20], Step 16500, Train Loss: 0.3114, Val Avg Corr: 0.7625
Epoch [2/20], Step 17000, Train Loss: 0.5546, Val Avg Corr: 0.7702
Epoch [2/20], Step 17500, Train Loss: 0.2887, Val Avg Corr: 0.7822
Epoch [2/20], Step 18000, Train Loss: 0.3768, Val Avg Corr: 0.7750
Epoch [2/20], Step 18500, Train Loss: 0.2872, Val Avg Corr: 0.7693
Epoch [2/20], Step 19000, Train Loss: 0.4333, Val Avg Corr: 0.7743
Epoch [2/20], Step 19500, Train Loss: 0.2759, Val Avg Corr: 0.7777
Epoch [2/20], Step 20000, Train Loss: 0.2952, Val Avg Corr: 0.7705
Epoch [2/20], Step 20500, Train Loss: 0.3458, Val Avg Corr: 0.7773
Trial change detected: 763 -> 764, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.4542, Val Avg Corr: 0.7746
Epoch [2/20], Step 21500, Train Loss: 0.4992, Val Avg Corr: 0.7753
Epoch [2/20], Step 22000, Train Loss: 0.3676, Val Avg Corr: 0.7738
Epoch [2/20], Step 22500, Train Loss: 0.3080, Val Avg Corr: 0.7766
Epoch [2/20], Step 23000, Train Loss: 0.3862, Val Avg Corr: 0.7741
Epoch [2/20], Step 23500, Train Loss: 0.4143, Val Avg Corr: 0.7762
Epoch [2/20], Step 24000, Train Loss: 0.3457, Val Avg Corr: 0.7781
Epoch [2/20], Step 24500, Train Loss: 0.3703, Val Avg Corr: 0.7799
Epoch [2/20], Step 25000, Train Loss: 0.2599, Val Avg Corr: 0.7812
Epoch [2/20], Step 25500, Train Loss: 0.3241, Val Avg Corr: 0.7713
Epoch [2/20], Step 26000, Train Loss: 0.3235, Val Avg Corr: 0.7845
  >>> New best validation model saved with Avg Corr: 0.7845 <<<
Epoch [2/20], Step 26500, Train Loss: 0.2652, Val Avg Corr: 0.7737
Epoch [2/20], Step 27000, Train Loss: 0.3850, Val Avg Corr: 0.7907
  >>> New best validation model saved with Avg Corr: 0.7907 <<<
Epoch [2/20], Step 27500, Train Loss: 0.3592, Val Avg Corr: 0.7921
  >>> New best validation model saved with Avg Corr: 0.7921 <<<
Epoch [2/20], Step 28000, Train Loss: 0.3655, Val Avg Corr: 0.7756
Epoch [2/20], Step 28500, Train Loss: 0.2621, Val Avg Corr: 0.7830
Epoch [2/20], Step 29000, Train Loss: 0.3118, Val Avg Corr: 0.7953
  >>> New best validation model saved with Avg Corr: 0.7953 <<<
Epoch [2/20], Step 29500, Train Loss: 0.3877, Val Avg Corr: 0.7873
Epoch [2/20], Step 30000, Train Loss: 0.3999, Val Avg Corr: 0.7938
Epoch [2/20], Step 30500, Train Loss: 0.3377, Val Avg Corr: 0.7935
Epoch [2/20], Step 31000, Train Loss: 0.3778, Val Avg Corr: 0.7885
Epoch [2/20], Step 31500, Train Loss: 0.3656, Val Avg Corr: 0.7865
Epoch [2/20], Step 32000, Train Loss: 0.3131, Val Avg Corr: 0.7913
Epoch [2/20], Step 32500, Train Loss: 0.3017, Val Avg Corr: 0.7886
Epoch [2/20], Step 33000, Train Loss: 0.4349, Val Avg Corr: 0.7855
Epoch [2/20], Step 33500, Train Loss: 0.2788, Val Avg Corr: 0.7849
Epoch [2/20], Step 34000, Train Loss: 0.2845, Val Avg Corr: 0.7832
Epoch [2/20], Step 34500, Train Loss: 0.2609, Val Avg Corr: 0.7861
Epoch [2/20], Step 35000, Train Loss: 0.3087, Val Avg Corr: 0.7919
Epoch [2/20], Step 35500, Train Loss: 0.2891, Val Avg Corr: 0.7852
Epoch [2/20], Step 36000, Train Loss: 0.2636, Val Avg Corr: 0.7876
Epoch [2/20], Step 36500, Train Loss: 0.3915, Val Avg Corr: 0.7906
Epoch [2/20], Step 37000, Train Loss: 0.4045, Val Avg Corr: 0.7933
Epoch [2/20], Step 37500, Train Loss: 0.3376, Val Avg Corr: 0.7886
Epoch [2/20], Step 38000, Train Loss: 0.4036, Val Avg Corr: 0.7806
Epoch [2/20], Step 38500, Train Loss: 0.2980, Val Avg Corr: 0.7828
Epoch [2/20], Step 39000, Train Loss: 0.3287, Val Avg Corr: 0.7903
Epoch [2/20], Step 39500, Train Loss: 0.3738, Val Avg Corr: 0.7884
Epoch [2/20], Step 40000, Train Loss: 0.2851, Val Avg Corr: 0.7770
Epoch [2/20], Step 40500, Train Loss: 0.2831, Val Avg Corr: 0.7827
Epoch [2/20], Step 41000, Train Loss: 0.3053, Val Avg Corr: 0.7895
Trial change detected: 1451 -> 1452, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3744, Val Avg Corr: 0.7946
Epoch [2/20], Step 42000, Train Loss: 0.3458, Val Avg Corr: 0.7866
Epoch [2/20], Step 42500, Train Loss: 0.3614, Val Avg Corr: 0.7904
Epoch [2/20], Step 43000, Train Loss: 0.3407, Val Avg Corr: 0.7871
Epoch [2/20], Step 43500, Train Loss: 0.3862, Val Avg Corr: 0.7794
Epoch [2/20], Step 44000, Train Loss: 0.3873, Val Avg Corr: 0.7830
Epoch [2/20], Step 44500, Train Loss: 0.3412, Val Avg Corr: 0.7909
Epoch [2/20], Step 45000, Train Loss: 0.3108, Val Avg Corr: 0.7815
Epoch [2/20], Step 45500, Train Loss: 0.4050, Val Avg Corr: 0.7877
Epoch [2/20], Step 46000, Train Loss: 0.3360, Val Avg Corr: 0.7842
Epoch [2/20], Step 46500, Train Loss: 0.3723, Val Avg Corr: 0.7892
Epoch [2/20], Step 47000, Train Loss: 0.2918, Val Avg Corr: 0.7969
  >>> New best validation model saved with Avg Corr: 0.7969 <<<
Epoch [2/20], Step 47500, Train Loss: 0.2752, Val Avg Corr: 0.7815
Epoch [2/20], Step 48000, Train Loss: 0.3224, Val Avg Corr: 0.7823
Epoch [2/20], Step 48500, Train Loss: 0.2934, Val Avg Corr: 0.7909
Epoch [2/20], Step 49000, Train Loss: 0.4247, Val Avg Corr: 0.7952
Epoch [2/20], Step 49500, Train Loss: 0.4215, Val Avg Corr: 0.7957
Epoch [2/20], Step 50000, Train Loss: 0.3283, Val Avg Corr: 0.7869
Epoch [2/20], Step 50500, Train Loss: 0.3634, Val Avg Corr: 0.8010
  >>> New best validation model saved with Avg Corr: 0.8010 <<<
Epoch [2/20], Step 51000, Train Loss: 0.3326, Val Avg Corr: 0.7927
Epoch [2/20], Step 51500, Train Loss: 0.2942, Val Avg Corr: 0.7933
Epoch [2/20], Step 52000, Train Loss: 0.2482, Val Avg Corr: 0.7874
Epoch [2/20], Step 52500, Train Loss: 0.4109, Val Avg Corr: 0.7878
Epoch [2/20], Step 53000, Train Loss: 0.3969, Val Avg Corr: 0.7879
Epoch [2/20], Step 53500, Train Loss: 0.4240, Val Avg Corr: 0.7927
Epoch [2/20], Step 54000, Train Loss: 0.3211, Val Avg Corr: 0.7860
Epoch [2/20], Step 54500, Train Loss: 0.4222, Val Avg Corr: 0.7895
Epoch [2/20], Step 55000, Train Loss: 0.4468, Val Avg Corr: 0.7927
Epoch [2/20], Step 55500, Train Loss: 0.3587, Val Avg Corr: 0.7980
Epoch [2/20], Step 56000, Train Loss: 0.3069, Val Avg Corr: 0.7884
Epoch [2/20], Step 56500, Train Loss: 0.4033, Val Avg Corr: 0.7958
Epoch [2/20], Step 57000, Train Loss: 0.3017, Val Avg Corr: 0.7975
Epoch [2/20], Step 57500, Train Loss: 0.3035, Val Avg Corr: 0.7918
Epoch [2/20], Step 58000, Train Loss: 0.2993, Val Avg Corr: 0.7988
Epoch [2/20], Step 58500, Train Loss: 0.3161, Val Avg Corr: 0.7962
Epoch [2/20], Step 59000, Train Loss: 0.3664, Val Avg Corr: 0.7993
Epoch [2/20], Step 59500, Train Loss: 0.2858, Val Avg Corr: 0.7950
Epoch [2/20], Step 60000, Train Loss: 0.2330, Val Avg Corr: 0.7911
Epoch [2/20], Step 60500, Train Loss: 0.3960, Val Avg Corr: 0.7897
Epoch [2/20], Step 61000, Train Loss: 0.3324, Val Avg Corr: 0.7986
Epoch [2/20], Step 61500, Train Loss: 0.3668, Val Avg Corr: 0.8060
  >>> New best validation model saved with Avg Corr: 0.8060 <<<
Trial change detected: 2139 -> 2141, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3543, Val Avg Corr: 0.8043
Epoch [2/20], Step 62500, Train Loss: 0.3616, Val Avg Corr: 0.8031
Epoch [2/20], Step 63000, Train Loss: 0.2962, Val Avg Corr: 0.8020
Epoch [2/20], Step 63500, Train Loss: 0.3436, Val Avg Corr: 0.8027
Epoch [2/20], Step 64000, Train Loss: 0.3242, Val Avg Corr: 0.8012
Epoch [2/20], Step 64500, Train Loss: 0.3529, Val Avg Corr: 0.7938
Epoch [2/20], Step 65000, Train Loss: 0.2672, Val Avg Corr: 0.8079
  >>> New best validation model saved with Avg Corr: 0.8079 <<<
Epoch [2/20], Step 65500, Train Loss: 0.3744, Val Avg Corr: 0.7995
Epoch [3/20], Step 500, Train Loss: 0.4121, Val Avg Corr: 0.7974
Epoch [3/20], Step 1000, Train Loss: 0.5103, Val Avg Corr: 0.7954
Epoch [3/20], Step 1500, Train Loss: 0.3574, Val Avg Corr: 0.8033
Epoch [3/20], Step 2000, Train Loss: 0.2685, Val Avg Corr: 0.7978
Epoch [3/20], Step 2500, Train Loss: 0.3203, Val Avg Corr: 0.8048
Epoch [3/20], Step 3000, Train Loss: 0.3410, Val Avg Corr: 0.8036
Epoch [3/20], Step 3500, Train Loss: 0.2324, Val Avg Corr: 0.8052
Epoch [3/20], Step 4000, Train Loss: 0.4127, Val Avg Corr: 0.8038
Epoch [3/20], Step 4500, Train Loss: 0.3913, Val Avg Corr: 0.8038
Epoch [3/20], Step 5000, Train Loss: 0.3195, Val Avg Corr: 0.8054
Epoch [3/20], Step 5500, Train Loss: 0.2602, Val Avg Corr: 0.7957
Epoch [3/20], Step 6000, Train Loss: 0.3165, Val Avg Corr: 0.7930
Epoch [3/20], Step 6500, Train Loss: 0.3746, Val Avg Corr: 0.7991
Epoch [3/20], Step 7000, Train Loss: 0.3345, Val Avg Corr: 0.7922
Epoch [3/20], Step 7500, Train Loss: 0.3974, Val Avg Corr: 0.8031
Epoch [3/20], Step 8000, Train Loss: 0.3015, Val Avg Corr: 0.8010
Epoch [3/20], Step 8500, Train Loss: 0.2791, Val Avg Corr: 0.7967
Epoch [3/20], Step 9000, Train Loss: 0.3214, Val Avg Corr: 0.7958
Epoch [3/20], Step 9500, Train Loss: 0.3210, Val Avg Corr: 0.7939
Epoch [3/20], Step 10000, Train Loss: 0.3565, Val Avg Corr: 0.7954
Epoch [3/20], Step 10500, Train Loss: 0.3514, Val Avg Corr: 0.7894
Epoch [3/20], Step 11000, Train Loss: 0.3512, Val Avg Corr: 0.7944
Epoch [3/20], Step 11500, Train Loss: 0.3501, Val Avg Corr: 0.7959
Epoch [3/20], Step 12000, Train Loss: 0.3695, Val Avg Corr: 0.7957
Epoch [3/20], Step 12500, Train Loss: 0.2751, Val Avg Corr: 0.7982
Epoch [3/20], Step 13000, Train Loss: 0.3516, Val Avg Corr: 0.7992
Epoch [3/20], Step 13500, Train Loss: 0.2621, Val Avg Corr: 0.8070
Epoch [3/20], Step 14000, Train Loss: 0.3442, Val Avg Corr: 0.7979
Epoch [3/20], Step 14500, Train Loss: 0.3102, Val Avg Corr: 0.7953
Epoch [3/20], Step 15000, Train Loss: 0.2855, Val Avg Corr: 0.7946
Epoch [3/20], Step 15500, Train Loss: 0.4225, Val Avg Corr: 0.8044
Epoch [3/20], Step 16000, Train Loss: 0.3255, Val Avg Corr: 0.8036
Epoch [3/20], Step 16500, Train Loss: 0.2819, Val Avg Corr: 0.7828
Epoch [3/20], Step 17000, Train Loss: 0.4689, Val Avg Corr: 0.7902
Epoch [3/20], Step 17500, Train Loss: 0.2672, Val Avg Corr: 0.7995
Epoch [3/20], Step 18000, Train Loss: 0.3243, Val Avg Corr: 0.8014
Epoch [3/20], Step 18500, Train Loss: 0.2680, Val Avg Corr: 0.7864
Epoch [3/20], Step 19000, Train Loss: 0.3987, Val Avg Corr: 0.8006
Epoch [3/20], Step 19500, Train Loss: 0.2486, Val Avg Corr: 0.7973
Epoch [3/20], Step 20000, Train Loss: 0.2648, Val Avg Corr: 0.7973
Epoch [3/20], Step 20500, Train Loss: 0.3002, Val Avg Corr: 0.7943
Trial change detected: 763 -> 764, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.4150, Val Avg Corr: 0.7923
Epoch [3/20], Step 21500, Train Loss: 0.4629, Val Avg Corr: 0.8059
Epoch [3/20], Step 22000, Train Loss: 0.3434, Val Avg Corr: 0.7929
Epoch [3/20], Step 22500, Train Loss: 0.2784, Val Avg Corr: 0.7956
Epoch [3/20], Step 23000, Train Loss: 0.3306, Val Avg Corr: 0.8020
Epoch [3/20], Step 23500, Train Loss: 0.3801, Val Avg Corr: 0.7993
Epoch [3/20], Step 24000, Train Loss: 0.2985, Val Avg Corr: 0.8056
Epoch [3/20], Step 24500, Train Loss: 0.3489, Val Avg Corr: 0.7971
Early stopping triggered after 24500 steps in epoch 3.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8079
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8232, Y=0.8004, Avg=0.8118

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 3) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.2192, Val Avg Corr: -0.0272
  >>> New best validation model saved with Avg Corr: -0.0272 <<<
Epoch [1/20], Step 1000, Train Loss: 1.4776, Val Avg Corr: 0.0289
  >>> New best validation model saved with Avg Corr: 0.0289 <<<
Epoch [1/20], Step 1500, Train Loss: 0.9977, Val Avg Corr: 0.0882
  >>> New best validation model saved with Avg Corr: 0.0882 <<<
Epoch [1/20], Step 2000, Train Loss: 1.2620, Val Avg Corr: 0.0620
Epoch [1/20], Step 2500, Train Loss: 0.9731, Val Avg Corr: 0.0692
Epoch [1/20], Step 3000, Train Loss: 0.9156, Val Avg Corr: 0.1122
  >>> New best validation model saved with Avg Corr: 0.1122 <<<
Epoch [1/20], Step 3500, Train Loss: 0.9176, Val Avg Corr: 0.1400
  >>> New best validation model saved with Avg Corr: 0.1400 <<<
Epoch [1/20], Step 4000, Train Loss: 0.8324, Val Avg Corr: 0.1820
  >>> New best validation model saved with Avg Corr: 0.1820 <<<
Epoch [1/20], Step 4500, Train Loss: 0.9250, Val Avg Corr: 0.1947
  >>> New best validation model saved with Avg Corr: 0.1947 <<<
Epoch [1/20], Step 5000, Train Loss: 0.9834, Val Avg Corr: 0.2282
  >>> New best validation model saved with Avg Corr: 0.2282 <<<
Epoch [1/20], Step 5500, Train Loss: 0.9255, Val Avg Corr: 0.2512
  >>> New best validation model saved with Avg Corr: 0.2512 <<<
Epoch [1/20], Step 6000, Train Loss: 0.8149, Val Avg Corr: 0.2753
  >>> New best validation model saved with Avg Corr: 0.2753 <<<
Epoch [1/20], Step 6500, Train Loss: 0.7423, Val Avg Corr: 0.2900
  >>> New best validation model saved with Avg Corr: 0.2900 <<<
Epoch [1/20], Step 7000, Train Loss: 0.9612, Val Avg Corr: 0.3175
  >>> New best validation model saved with Avg Corr: 0.3175 <<<
Epoch [1/20], Step 7500, Train Loss: 0.8289, Val Avg Corr: 0.3246
  >>> New best validation model saved with Avg Corr: 0.3246 <<<
Epoch [1/20], Step 8000, Train Loss: 0.8490, Val Avg Corr: 0.3266
  >>> New best validation model saved with Avg Corr: 0.3266 <<<
Epoch [1/20], Step 8500, Train Loss: 0.8697, Val Avg Corr: 0.3877
  >>> New best validation model saved with Avg Corr: 0.3877 <<<
Epoch [1/20], Step 9000, Train Loss: 0.8257, Val Avg Corr: 0.3906
  >>> New best validation model saved with Avg Corr: 0.3906 <<<
Epoch [1/20], Step 9500, Train Loss: 0.7644, Val Avg Corr: 0.3906
  >>> New best validation model saved with Avg Corr: 0.3906 <<<
Epoch [1/20], Step 10000, Train Loss: 0.8178, Val Avg Corr: 0.3685
Epoch [1/20], Step 10500, Train Loss: 0.7513, Val Avg Corr: 0.3859
Epoch [1/20], Step 11000, Train Loss: 0.8834, Val Avg Corr: 0.4100
  >>> New best validation model saved with Avg Corr: 0.4100 <<<
Epoch [1/20], Step 11500, Train Loss: 0.7277, Val Avg Corr: 0.4466
  >>> New best validation model saved with Avg Corr: 0.4466 <<<
Epoch [1/20], Step 12000, Train Loss: 0.7210, Val Avg Corr: 0.5069
  >>> New best validation model saved with Avg Corr: 0.5069 <<<
Epoch [1/20], Step 12500, Train Loss: 0.8087, Val Avg Corr: 0.4864
Epoch [1/20], Step 13000, Train Loss: 0.6724, Val Avg Corr: 0.5111
  >>> New best validation model saved with Avg Corr: 0.5111 <<<
Epoch [1/20], Step 13500, Train Loss: 0.7207, Val Avg Corr: 0.5415
  >>> New best validation model saved with Avg Corr: 0.5415 <<<
Epoch [1/20], Step 14000, Train Loss: 0.7270, Val Avg Corr: 0.5352
Epoch [1/20], Step 14500, Train Loss: 0.8660, Val Avg Corr: 0.5487
  >>> New best validation model saved with Avg Corr: 0.5487 <<<
Epoch [1/20], Step 15000, Train Loss: 0.6004, Val Avg Corr: 0.5808
  >>> New best validation model saved with Avg Corr: 0.5808 <<<
Epoch [1/20], Step 15500, Train Loss: 0.6832, Val Avg Corr: 0.5589
Epoch [1/20], Step 16000, Train Loss: 0.7428, Val Avg Corr: 0.5791
Epoch [1/20], Step 16500, Train Loss: 0.6981, Val Avg Corr: 0.5591
Epoch [1/20], Step 17000, Train Loss: 0.6501, Val Avg Corr: 0.5837
  >>> New best validation model saved with Avg Corr: 0.5837 <<<
Epoch [1/20], Step 17500, Train Loss: 0.7444, Val Avg Corr: 0.6052
  >>> New best validation model saved with Avg Corr: 0.6052 <<<
Epoch [1/20], Step 18000, Train Loss: 0.5335, Val Avg Corr: 0.6069
  >>> New best validation model saved with Avg Corr: 0.6069 <<<
Epoch [1/20], Step 18500, Train Loss: 0.7001, Val Avg Corr: 0.6233
  >>> New best validation model saved with Avg Corr: 0.6233 <<<
Epoch [1/20], Step 19000, Train Loss: 0.5312, Val Avg Corr: 0.6153
Epoch [1/20], Step 19500, Train Loss: 0.6995, Val Avg Corr: 0.6300
  >>> New best validation model saved with Avg Corr: 0.6300 <<<
Epoch [1/20], Step 20000, Train Loss: 0.4699, Val Avg Corr: 0.6224
Epoch [1/20], Step 20500, Train Loss: 0.5263, Val Avg Corr: 0.6315
  >>> New best validation model saved with Avg Corr: 0.6315 <<<
Trial change detected: 733 -> 734, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.4956, Val Avg Corr: 0.6547
  >>> New best validation model saved with Avg Corr: 0.6547 <<<
Epoch [1/20], Step 21500, Train Loss: 0.5927, Val Avg Corr: 0.6388
Epoch [1/20], Step 22000, Train Loss: 0.6206, Val Avg Corr: 0.6386
Epoch [1/20], Step 22500, Train Loss: 0.6199, Val Avg Corr: 0.6505
Epoch [1/20], Step 23000, Train Loss: 0.4014, Val Avg Corr: 0.6456
Epoch [1/20], Step 23500, Train Loss: 0.5659, Val Avg Corr: 0.6661
  >>> New best validation model saved with Avg Corr: 0.6661 <<<
Epoch [1/20], Step 24000, Train Loss: 0.6797, Val Avg Corr: 0.6591
Epoch [1/20], Step 24500, Train Loss: 0.5328, Val Avg Corr: 0.6772
  >>> New best validation model saved with Avg Corr: 0.6772 <<<
Epoch [1/20], Step 25000, Train Loss: 0.6295, Val Avg Corr: 0.6840
  >>> New best validation model saved with Avg Corr: 0.6840 <<<
Epoch [1/20], Step 25500, Train Loss: 0.4300, Val Avg Corr: 0.6735
Epoch [1/20], Step 26000, Train Loss: 0.3281, Val Avg Corr: 0.6786
Epoch [1/20], Step 26500, Train Loss: 0.4107, Val Avg Corr: 0.6759
Epoch [1/20], Step 27000, Train Loss: 0.5656, Val Avg Corr: 0.6866
  >>> New best validation model saved with Avg Corr: 0.6866 <<<
Epoch [1/20], Step 27500, Train Loss: 0.4736, Val Avg Corr: 0.6912
  >>> New best validation model saved with Avg Corr: 0.6912 <<<
Epoch [1/20], Step 28000, Train Loss: 0.3975, Val Avg Corr: 0.6866
Epoch [1/20], Step 28500, Train Loss: 0.4169, Val Avg Corr: 0.6919
  >>> New best validation model saved with Avg Corr: 0.6919 <<<
Epoch [1/20], Step 29000, Train Loss: 0.3158, Val Avg Corr: 0.6994
  >>> New best validation model saved with Avg Corr: 0.6994 <<<
Epoch [1/20], Step 29500, Train Loss: 0.4908, Val Avg Corr: 0.6981
Epoch [1/20], Step 30000, Train Loss: 0.5267, Val Avg Corr: 0.7044
  >>> New best validation model saved with Avg Corr: 0.7044 <<<
Epoch [1/20], Step 30500, Train Loss: 0.4628, Val Avg Corr: 0.7091
  >>> New best validation model saved with Avg Corr: 0.7091 <<<
Epoch [1/20], Step 31000, Train Loss: 0.4948, Val Avg Corr: 0.6962
Epoch [1/20], Step 31500, Train Loss: 0.4295, Val Avg Corr: 0.7046
Epoch [1/20], Step 32000, Train Loss: 0.4857, Val Avg Corr: 0.7119
  >>> New best validation model saved with Avg Corr: 0.7119 <<<
Epoch [1/20], Step 32500, Train Loss: 0.4194, Val Avg Corr: 0.7010
Epoch [1/20], Step 33000, Train Loss: 0.3958, Val Avg Corr: 0.7163
  >>> New best validation model saved with Avg Corr: 0.7163 <<<
Epoch [1/20], Step 33500, Train Loss: 0.5176, Val Avg Corr: 0.7008
Epoch [1/20], Step 34000, Train Loss: 0.3876, Val Avg Corr: 0.7111
Epoch [1/20], Step 34500, Train Loss: 0.3649, Val Avg Corr: 0.7115
Epoch [1/20], Step 35000, Train Loss: 0.3652, Val Avg Corr: 0.7175
  >>> New best validation model saved with Avg Corr: 0.7175 <<<
Epoch [1/20], Step 35500, Train Loss: 0.3361, Val Avg Corr: 0.7184
  >>> New best validation model saved with Avg Corr: 0.7184 <<<
Epoch [1/20], Step 36000, Train Loss: 0.4024, Val Avg Corr: 0.7235
  >>> New best validation model saved with Avg Corr: 0.7235 <<<
Epoch [1/20], Step 36500, Train Loss: 0.3275, Val Avg Corr: 0.7177
Epoch [1/20], Step 37000, Train Loss: 0.6087, Val Avg Corr: 0.7147
Epoch [1/20], Step 37500, Train Loss: 0.5046, Val Avg Corr: 0.7165
Epoch [1/20], Step 38000, Train Loss: 0.3821, Val Avg Corr: 0.7246
  >>> New best validation model saved with Avg Corr: 0.7246 <<<
Epoch [1/20], Step 38500, Train Loss: 0.4701, Val Avg Corr: 0.7213
Epoch [1/20], Step 39000, Train Loss: 0.4245, Val Avg Corr: 0.7231
Epoch [1/20], Step 39500, Train Loss: 0.4625, Val Avg Corr: 0.7245
Epoch [1/20], Step 40000, Train Loss: 0.3719, Val Avg Corr: 0.7278
  >>> New best validation model saved with Avg Corr: 0.7278 <<<
Epoch [1/20], Step 40500, Train Loss: 0.3365, Val Avg Corr: 0.7223
Epoch [1/20], Step 41000, Train Loss: 0.3285, Val Avg Corr: 0.7247
Trial change detected: 1437 -> 1438, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.4193, Val Avg Corr: 0.7269
Epoch [1/20], Step 42000, Train Loss: 0.4323, Val Avg Corr: 0.7297
  >>> New best validation model saved with Avg Corr: 0.7297 <<<
Epoch [1/20], Step 42500, Train Loss: 0.3359, Val Avg Corr: 0.7306
  >>> New best validation model saved with Avg Corr: 0.7306 <<<
Epoch [1/20], Step 43000, Train Loss: 0.5382, Val Avg Corr: 0.7409
  >>> New best validation model saved with Avg Corr: 0.7409 <<<
Epoch [1/20], Step 43500, Train Loss: 0.3689, Val Avg Corr: 0.7367
Epoch [1/20], Step 44000, Train Loss: 0.4189, Val Avg Corr: 0.7333
Epoch [1/20], Step 44500, Train Loss: 0.4414, Val Avg Corr: 0.7383
Epoch [1/20], Step 45000, Train Loss: 0.4601, Val Avg Corr: 0.7359
Epoch [1/20], Step 45500, Train Loss: 0.4507, Val Avg Corr: 0.7362
Epoch [1/20], Step 46000, Train Loss: 0.4962, Val Avg Corr: 0.7392
Epoch [1/20], Step 46500, Train Loss: 0.4069, Val Avg Corr: 0.7318
Epoch [1/20], Step 47000, Train Loss: 0.2250, Val Avg Corr: 0.7407
Epoch [1/20], Step 47500, Train Loss: 0.4155, Val Avg Corr: 0.7379
Epoch [1/20], Step 48000, Train Loss: 0.3987, Val Avg Corr: 0.7389
Epoch [1/20], Step 48500, Train Loss: 0.4417, Val Avg Corr: 0.7357
Epoch [1/20], Step 49000, Train Loss: 0.3960, Val Avg Corr: 0.7475
  >>> New best validation model saved with Avg Corr: 0.7475 <<<
Epoch [1/20], Step 49500, Train Loss: 0.3459, Val Avg Corr: 0.7232
Epoch [1/20], Step 50000, Train Loss: 0.4751, Val Avg Corr: 0.7441
Epoch [1/20], Step 50500, Train Loss: 0.3255, Val Avg Corr: 0.7399
Epoch [1/20], Step 51000, Train Loss: 0.3458, Val Avg Corr: 0.7439
Epoch [1/20], Step 51500, Train Loss: 0.4668, Val Avg Corr: 0.7364
Epoch [1/20], Step 52000, Train Loss: 0.3559, Val Avg Corr: 0.7465
Epoch [1/20], Step 52500, Train Loss: 0.4282, Val Avg Corr: 0.7459
Epoch [1/20], Step 53000, Train Loss: 0.4798, Val Avg Corr: 0.7391
Epoch [1/20], Step 53500, Train Loss: 0.4056, Val Avg Corr: 0.7424
Epoch [1/20], Step 54000, Train Loss: 0.4290, Val Avg Corr: 0.7415
Epoch [1/20], Step 54500, Train Loss: 0.4440, Val Avg Corr: 0.7500
  >>> New best validation model saved with Avg Corr: 0.7500 <<<
Epoch [1/20], Step 55000, Train Loss: 0.4086, Val Avg Corr: 0.7493
Epoch [1/20], Step 55500, Train Loss: 0.3586, Val Avg Corr: 0.7545
  >>> New best validation model saved with Avg Corr: 0.7545 <<<
Epoch [1/20], Step 56000, Train Loss: 0.5454, Val Avg Corr: 0.7445
Epoch [1/20], Step 56500, Train Loss: 0.4795, Val Avg Corr: 0.7471
Epoch [1/20], Step 57000, Train Loss: 0.4652, Val Avg Corr: 0.7529
Epoch [1/20], Step 57500, Train Loss: 0.3574, Val Avg Corr: 0.7580
  >>> New best validation model saved with Avg Corr: 0.7580 <<<
Epoch [1/20], Step 58000, Train Loss: 0.4778, Val Avg Corr: 0.7571
Epoch [1/20], Step 58500, Train Loss: 0.3949, Val Avg Corr: 0.7472
Epoch [1/20], Step 59000, Train Loss: 0.3294, Val Avg Corr: 0.7516
Epoch [1/20], Step 59500, Train Loss: 0.4426, Val Avg Corr: 0.7518
Epoch [1/20], Step 60000, Train Loss: 0.3262, Val Avg Corr: 0.7599
  >>> New best validation model saved with Avg Corr: 0.7599 <<<
Epoch [1/20], Step 60500, Train Loss: 0.3604, Val Avg Corr: 0.7420
Epoch [1/20], Step 61000, Train Loss: 0.3085, Val Avg Corr: 0.7505
Epoch [1/20], Step 61500, Train Loss: 0.3811, Val Avg Corr: 0.7396
Trial change detected: 2146 -> 2149, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3502, Val Avg Corr: 0.7522
Epoch [1/20], Step 62500, Train Loss: 0.3609, Val Avg Corr: 0.7601
  >>> New best validation model saved with Avg Corr: 0.7601 <<<
Epoch [1/20], Step 63000, Train Loss: 0.3373, Val Avg Corr: 0.7516
Epoch [1/20], Step 63500, Train Loss: 0.3495, Val Avg Corr: 0.7587
Epoch [1/20], Step 64000, Train Loss: 0.4691, Val Avg Corr: 0.7593
Epoch [1/20], Step 64500, Train Loss: 0.3800, Val Avg Corr: 0.7482
Epoch [1/20], Step 65000, Train Loss: 0.3187, Val Avg Corr: 0.7554
Epoch [1/20], Step 65500, Train Loss: 0.4397, Val Avg Corr: 0.7586
Epoch [2/20], Step 500, Train Loss: 0.3335, Val Avg Corr: 0.7598
Epoch [2/20], Step 1000, Train Loss: 0.6591, Val Avg Corr: 0.7586
Epoch [2/20], Step 1500, Train Loss: 0.3995, Val Avg Corr: 0.7633
  >>> New best validation model saved with Avg Corr: 0.7633 <<<
Epoch [2/20], Step 2000, Train Loss: 0.4145, Val Avg Corr: 0.7629
Epoch [2/20], Step 2500, Train Loss: 0.3095, Val Avg Corr: 0.7616
Epoch [2/20], Step 3000, Train Loss: 0.3341, Val Avg Corr: 0.7654
  >>> New best validation model saved with Avg Corr: 0.7654 <<<
Epoch [2/20], Step 3500, Train Loss: 0.3776, Val Avg Corr: 0.7656
  >>> New best validation model saved with Avg Corr: 0.7656 <<<
Epoch [2/20], Step 4000, Train Loss: 0.3901, Val Avg Corr: 0.7679
  >>> New best validation model saved with Avg Corr: 0.7679 <<<
Epoch [2/20], Step 4500, Train Loss: 0.3772, Val Avg Corr: 0.7599
Epoch [2/20], Step 5000, Train Loss: 0.4976, Val Avg Corr: 0.7627
Epoch [2/20], Step 5500, Train Loss: 0.2966, Val Avg Corr: 0.7578
Epoch [2/20], Step 6000, Train Loss: 0.2750, Val Avg Corr: 0.7621
Epoch [2/20], Step 6500, Train Loss: 0.3141, Val Avg Corr: 0.7594
Epoch [2/20], Step 7000, Train Loss: 0.4020, Val Avg Corr: 0.7611
Epoch [2/20], Step 7500, Train Loss: 0.3478, Val Avg Corr: 0.7683
  >>> New best validation model saved with Avg Corr: 0.7683 <<<
Epoch [2/20], Step 8000, Train Loss: 0.3815, Val Avg Corr: 0.7575
Epoch [2/20], Step 8500, Train Loss: 0.4560, Val Avg Corr: 0.7664
Epoch [2/20], Step 9000, Train Loss: 0.3861, Val Avg Corr: 0.7672
Epoch [2/20], Step 9500, Train Loss: 0.2815, Val Avg Corr: 0.7674
Epoch [2/20], Step 10000, Train Loss: 0.3738, Val Avg Corr: 0.7661
Epoch [2/20], Step 10500, Train Loss: 0.3297, Val Avg Corr: 0.7574
Epoch [2/20], Step 11000, Train Loss: 0.3460, Val Avg Corr: 0.7667
Epoch [2/20], Step 11500, Train Loss: 0.3660, Val Avg Corr: 0.7672
Epoch [2/20], Step 12000, Train Loss: 0.3984, Val Avg Corr: 0.7674
Epoch [2/20], Step 12500, Train Loss: 0.4925, Val Avg Corr: 0.7716
  >>> New best validation model saved with Avg Corr: 0.7716 <<<
Epoch [2/20], Step 13000, Train Loss: 0.3081, Val Avg Corr: 0.7654
Epoch [2/20], Step 13500, Train Loss: 0.3816, Val Avg Corr: 0.7718
  >>> New best validation model saved with Avg Corr: 0.7718 <<<
Epoch [2/20], Step 14000, Train Loss: 0.3425, Val Avg Corr: 0.7667
Epoch [2/20], Step 14500, Train Loss: 0.3989, Val Avg Corr: 0.7652
Epoch [2/20], Step 15000, Train Loss: 0.3415, Val Avg Corr: 0.7699
Epoch [2/20], Step 15500, Train Loss: 0.4210, Val Avg Corr: 0.7632
Epoch [2/20], Step 16000, Train Loss: 0.4202, Val Avg Corr: 0.7670
Epoch [2/20], Step 16500, Train Loss: 0.3557, Val Avg Corr: 0.7628
Epoch [2/20], Step 17000, Train Loss: 0.3909, Val Avg Corr: 0.7617
Epoch [2/20], Step 17500, Train Loss: 0.4812, Val Avg Corr: 0.7672
Epoch [2/20], Step 18000, Train Loss: 0.2936, Val Avg Corr: 0.7718
Epoch [2/20], Step 18500, Train Loss: 0.4455, Val Avg Corr: 0.7632
Epoch [2/20], Step 19000, Train Loss: 0.2994, Val Avg Corr: 0.7635
Epoch [2/20], Step 19500, Train Loss: 0.4637, Val Avg Corr: 0.7727
  >>> New best validation model saved with Avg Corr: 0.7727 <<<
Epoch [2/20], Step 20000, Train Loss: 0.2770, Val Avg Corr: 0.7723
Epoch [2/20], Step 20500, Train Loss: 0.2988, Val Avg Corr: 0.7758
  >>> New best validation model saved with Avg Corr: 0.7758 <<<
Trial change detected: 733 -> 734, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.3457, Val Avg Corr: 0.7734
Epoch [2/20], Step 21500, Train Loss: 0.3921, Val Avg Corr: 0.7735
Epoch [2/20], Step 22000, Train Loss: 0.4808, Val Avg Corr: 0.7540
Epoch [2/20], Step 22500, Train Loss: 0.4166, Val Avg Corr: 0.7727
Epoch [2/20], Step 23000, Train Loss: 0.3442, Val Avg Corr: 0.7751
Epoch [2/20], Step 23500, Train Loss: 0.3616, Val Avg Corr: 0.7695
Epoch [2/20], Step 24000, Train Loss: 0.5053, Val Avg Corr: 0.7721
Epoch [2/20], Step 24500, Train Loss: 0.3069, Val Avg Corr: 0.7750
Epoch [2/20], Step 25000, Train Loss: 0.4254, Val Avg Corr: 0.7756
Epoch [2/20], Step 25500, Train Loss: 0.2838, Val Avg Corr: 0.7674
Epoch [2/20], Step 26000, Train Loss: 0.2713, Val Avg Corr: 0.7683
Epoch [2/20], Step 26500, Train Loss: 0.3097, Val Avg Corr: 0.7722
Epoch [2/20], Step 27000, Train Loss: 0.4042, Val Avg Corr: 0.7770
  >>> New best validation model saved with Avg Corr: 0.7770 <<<
Epoch [2/20], Step 27500, Train Loss: 0.3934, Val Avg Corr: 0.7718
Epoch [2/20], Step 28000, Train Loss: 0.3399, Val Avg Corr: 0.7704
Epoch [2/20], Step 28500, Train Loss: 0.2990, Val Avg Corr: 0.7760
Epoch [2/20], Step 29000, Train Loss: 0.2340, Val Avg Corr: 0.7717
Epoch [2/20], Step 29500, Train Loss: 0.3602, Val Avg Corr: 0.7751
Epoch [2/20], Step 30000, Train Loss: 0.4034, Val Avg Corr: 0.7753
Epoch [2/20], Step 30500, Train Loss: 0.3791, Val Avg Corr: 0.7755
Epoch [2/20], Step 31000, Train Loss: 0.3733, Val Avg Corr: 0.7694
Epoch [2/20], Step 31500, Train Loss: 0.3606, Val Avg Corr: 0.7669
Epoch [2/20], Step 32000, Train Loss: 0.3877, Val Avg Corr: 0.7832
  >>> New best validation model saved with Avg Corr: 0.7832 <<<
Epoch [2/20], Step 32500, Train Loss: 0.3459, Val Avg Corr: 0.7700
Epoch [2/20], Step 33000, Train Loss: 0.3071, Val Avg Corr: 0.7781
Epoch [2/20], Step 33500, Train Loss: 0.4298, Val Avg Corr: 0.7589
Epoch [2/20], Step 34000, Train Loss: 0.3031, Val Avg Corr: 0.7753
Epoch [2/20], Step 34500, Train Loss: 0.3179, Val Avg Corr: 0.7706
Epoch [2/20], Step 35000, Train Loss: 0.2924, Val Avg Corr: 0.7777
Epoch [2/20], Step 35500, Train Loss: 0.2517, Val Avg Corr: 0.7747
Epoch [2/20], Step 36000, Train Loss: 0.3139, Val Avg Corr: 0.7771
Epoch [2/20], Step 36500, Train Loss: 0.2287, Val Avg Corr: 0.7715
Epoch [2/20], Step 37000, Train Loss: 0.4567, Val Avg Corr: 0.7734
Epoch [2/20], Step 37500, Train Loss: 0.3923, Val Avg Corr: 0.7745
Epoch [2/20], Step 38000, Train Loss: 0.3306, Val Avg Corr: 0.7781
Epoch [2/20], Step 38500, Train Loss: 0.3931, Val Avg Corr: 0.7766
Epoch [2/20], Step 39000, Train Loss: 0.3449, Val Avg Corr: 0.7758
Epoch [2/20], Step 39500, Train Loss: 0.3821, Val Avg Corr: 0.7733
Epoch [2/20], Step 40000, Train Loss: 0.3125, Val Avg Corr: 0.7729
Epoch [2/20], Step 40500, Train Loss: 0.2855, Val Avg Corr: 0.7756
Epoch [2/20], Step 41000, Train Loss: 0.3001, Val Avg Corr: 0.7867
  >>> New best validation model saved with Avg Corr: 0.7867 <<<
Trial change detected: 1437 -> 1438, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3303, Val Avg Corr: 0.7797
Epoch [2/20], Step 42000, Train Loss: 0.3432, Val Avg Corr: 0.7819
Epoch [2/20], Step 42500, Train Loss: 0.2781, Val Avg Corr: 0.7823
Epoch [2/20], Step 43000, Train Loss: 0.4137, Val Avg Corr: 0.7816
Epoch [2/20], Step 43500, Train Loss: 0.3075, Val Avg Corr: 0.7791
Epoch [2/20], Step 44000, Train Loss: 0.3577, Val Avg Corr: 0.7786
Epoch [2/20], Step 44500, Train Loss: 0.3984, Val Avg Corr: 0.7819
Epoch [2/20], Step 45000, Train Loss: 0.3645, Val Avg Corr: 0.7727
Epoch [2/20], Step 45500, Train Loss: 0.3784, Val Avg Corr: 0.7798
Epoch [2/20], Step 46000, Train Loss: 0.4151, Val Avg Corr: 0.7867
  >>> New best validation model saved with Avg Corr: 0.7867 <<<
Epoch [2/20], Step 46500, Train Loss: 0.3210, Val Avg Corr: 0.7702
Epoch [2/20], Step 47000, Train Loss: 0.2021, Val Avg Corr: 0.7776
Epoch [2/20], Step 47500, Train Loss: 0.3295, Val Avg Corr: 0.7690
Epoch [2/20], Step 48000, Train Loss: 0.3627, Val Avg Corr: 0.7729
Epoch [2/20], Step 48500, Train Loss: 0.3736, Val Avg Corr: 0.7770
Epoch [2/20], Step 49000, Train Loss: 0.3579, Val Avg Corr: 0.7804
Epoch [2/20], Step 49500, Train Loss: 0.3140, Val Avg Corr: 0.7676
Epoch [2/20], Step 50000, Train Loss: 0.4138, Val Avg Corr: 0.7738
Epoch [2/20], Step 50500, Train Loss: 0.2484, Val Avg Corr: 0.7772
Epoch [2/20], Step 51000, Train Loss: 0.3206, Val Avg Corr: 0.7771
Epoch [2/20], Step 51500, Train Loss: 0.3790, Val Avg Corr: 0.7768
Epoch [2/20], Step 52000, Train Loss: 0.3120, Val Avg Corr: 0.7733
Epoch [2/20], Step 52500, Train Loss: 0.3879, Val Avg Corr: 0.7847
Epoch [2/20], Step 53000, Train Loss: 0.4021, Val Avg Corr: 0.7790
Epoch [2/20], Step 53500, Train Loss: 0.3665, Val Avg Corr: 0.7720
Epoch [2/20], Step 54000, Train Loss: 0.3747, Val Avg Corr: 0.7704
Epoch [2/20], Step 54500, Train Loss: 0.3798, Val Avg Corr: 0.7768
Epoch [2/20], Step 55000, Train Loss: 0.3618, Val Avg Corr: 0.7805
Epoch [2/20], Step 55500, Train Loss: 0.3049, Val Avg Corr: 0.7892
  >>> New best validation model saved with Avg Corr: 0.7892 <<<
Epoch [2/20], Step 56000, Train Loss: 0.4522, Val Avg Corr: 0.7788
Epoch [2/20], Step 56500, Train Loss: 0.4257, Val Avg Corr: 0.7852
Epoch [2/20], Step 57000, Train Loss: 0.3852, Val Avg Corr: 0.7720
Epoch [2/20], Step 57500, Train Loss: 0.3168, Val Avg Corr: 0.7848
Epoch [2/20], Step 58000, Train Loss: 0.4050, Val Avg Corr: 0.7939
  >>> New best validation model saved with Avg Corr: 0.7939 <<<
Epoch [2/20], Step 58500, Train Loss: 0.3556, Val Avg Corr: 0.7794
Epoch [2/20], Step 59000, Train Loss: 0.3084, Val Avg Corr: 0.7845
Epoch [2/20], Step 59500, Train Loss: 0.3819, Val Avg Corr: 0.7834
Epoch [2/20], Step 60000, Train Loss: 0.2807, Val Avg Corr: 0.7823
Epoch [2/20], Step 60500, Train Loss: 0.3402, Val Avg Corr: 0.7691
Epoch [2/20], Step 61000, Train Loss: 0.2753, Val Avg Corr: 0.7779
Epoch [2/20], Step 61500, Train Loss: 0.3437, Val Avg Corr: 0.7773
Trial change detected: 2146 -> 2149, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.2924, Val Avg Corr: 0.7811
Epoch [2/20], Step 62500, Train Loss: 0.3261, Val Avg Corr: 0.7847
Epoch [2/20], Step 63000, Train Loss: 0.3198, Val Avg Corr: 0.7821
Epoch [2/20], Step 63500, Train Loss: 0.3260, Val Avg Corr: 0.7843
Epoch [2/20], Step 64000, Train Loss: 0.4019, Val Avg Corr: 0.7827
Epoch [2/20], Step 64500, Train Loss: 0.3375, Val Avg Corr: 0.7726
Epoch [2/20], Step 65000, Train Loss: 0.2986, Val Avg Corr: 0.7873
Epoch [2/20], Step 65500, Train Loss: 0.3801, Val Avg Corr: 0.7866
Epoch [3/20], Step 500, Train Loss: 0.3203, Val Avg Corr: 0.7836
Epoch [3/20], Step 1000, Train Loss: 0.5901, Val Avg Corr: 0.7771
Epoch [3/20], Step 1500, Train Loss: 0.3501, Val Avg Corr: 0.7860
Epoch [3/20], Step 2000, Train Loss: 0.3682, Val Avg Corr: 0.7856
Epoch [3/20], Step 2500, Train Loss: 0.2592, Val Avg Corr: 0.7870
Epoch [3/20], Step 3000, Train Loss: 0.3037, Val Avg Corr: 0.7871
Epoch [3/20], Step 3500, Train Loss: 0.3850, Val Avg Corr: 0.7832
Epoch [3/20], Step 4000, Train Loss: 0.3378, Val Avg Corr: 0.7862
Epoch [3/20], Step 4500, Train Loss: 0.3242, Val Avg Corr: 0.7816
Epoch [3/20], Step 5000, Train Loss: 0.4807, Val Avg Corr: 0.7908
Epoch [3/20], Step 5500, Train Loss: 0.2726, Val Avg Corr: 0.7881
Epoch [3/20], Step 6000, Train Loss: 0.2480, Val Avg Corr: 0.7885
Epoch [3/20], Step 6500, Train Loss: 0.2885, Val Avg Corr: 0.7893
Epoch [3/20], Step 7000, Train Loss: 0.3579, Val Avg Corr: 0.7861
Epoch [3/20], Step 7500, Train Loss: 0.3293, Val Avg Corr: 0.7881
Epoch [3/20], Step 8000, Train Loss: 0.3505, Val Avg Corr: 0.7813
Epoch [3/20], Step 8500, Train Loss: 0.4065, Val Avg Corr: 0.7869
Epoch [3/20], Step 9000, Train Loss: 0.3359, Val Avg Corr: 0.7782
Epoch [3/20], Step 9500, Train Loss: 0.2541, Val Avg Corr: 0.7802
Epoch [3/20], Step 10000, Train Loss: 0.3280, Val Avg Corr: 0.7827
Epoch [3/20], Step 10500, Train Loss: 0.3202, Val Avg Corr: 0.7792
Epoch [3/20], Step 11000, Train Loss: 0.3225, Val Avg Corr: 0.7809
Epoch [3/20], Step 11500, Train Loss: 0.3286, Val Avg Corr: 0.7850
Epoch [3/20], Step 12000, Train Loss: 0.3561, Val Avg Corr: 0.7839
Epoch [3/20], Step 12500, Train Loss: 0.4227, Val Avg Corr: 0.7869
Epoch [3/20], Step 13000, Train Loss: 0.2710, Val Avg Corr: 0.7841
Epoch [3/20], Step 13500, Train Loss: 0.3391, Val Avg Corr: 0.7922
Epoch [3/20], Step 14000, Train Loss: 0.3036, Val Avg Corr: 0.7905
Epoch [3/20], Step 14500, Train Loss: 0.3413, Val Avg Corr: 0.7869
Epoch [3/20], Step 15000, Train Loss: 0.3085, Val Avg Corr: 0.7850
Epoch [3/20], Step 15500, Train Loss: 0.3861, Val Avg Corr: 0.7802
Epoch [3/20], Step 16000, Train Loss: 0.4065, Val Avg Corr: 0.7859
Epoch [3/20], Step 16500, Train Loss: 0.3043, Val Avg Corr: 0.7867
Epoch [3/20], Step 17000, Train Loss: 0.3466, Val Avg Corr: 0.7812
Epoch [3/20], Step 17500, Train Loss: 0.4152, Val Avg Corr: 0.7907
Early stopping triggered after 17500 steps in epoch 3.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.7939
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8339, Y=0.7869, Avg=0.8104

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 4) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.2091, Val Avg Corr: 0.0370
  >>> New best validation model saved with Avg Corr: 0.0370 <<<
Epoch [1/20], Step 1000, Train Loss: 0.9869, Val Avg Corr: 0.0669
  >>> New best validation model saved with Avg Corr: 0.0669 <<<
Epoch [1/20], Step 1500, Train Loss: 0.9902, Val Avg Corr: 0.0901
  >>> New best validation model saved with Avg Corr: 0.0901 <<<
Epoch [1/20], Step 2000, Train Loss: 1.0434, Val Avg Corr: 0.0888
Epoch [1/20], Step 2500, Train Loss: 0.8376, Val Avg Corr: 0.1207
  >>> New best validation model saved with Avg Corr: 0.1207 <<<
Epoch [1/20], Step 3000, Train Loss: 0.9223, Val Avg Corr: 0.1403
  >>> New best validation model saved with Avg Corr: 0.1403 <<<
Epoch [1/20], Step 3500, Train Loss: 0.9907, Val Avg Corr: 0.1339
Epoch [1/20], Step 4000, Train Loss: 0.7857, Val Avg Corr: 0.2066
  >>> New best validation model saved with Avg Corr: 0.2066 <<<
Epoch [1/20], Step 4500, Train Loss: 0.9226, Val Avg Corr: 0.2456
  >>> New best validation model saved with Avg Corr: 0.2456 <<<
Epoch [1/20], Step 5000, Train Loss: 1.1759, Val Avg Corr: 0.2299
Epoch [1/20], Step 5500, Train Loss: 0.9331, Val Avg Corr: 0.2731
  >>> New best validation model saved with Avg Corr: 0.2731 <<<
Epoch [1/20], Step 6000, Train Loss: 0.8571, Val Avg Corr: 0.2928
  >>> New best validation model saved with Avg Corr: 0.2928 <<<
Epoch [1/20], Step 6500, Train Loss: 0.7747, Val Avg Corr: 0.3254
  >>> New best validation model saved with Avg Corr: 0.3254 <<<
Epoch [1/20], Step 7000, Train Loss: 0.7977, Val Avg Corr: 0.3225
Epoch [1/20], Step 7500, Train Loss: 0.8526, Val Avg Corr: 0.3860
  >>> New best validation model saved with Avg Corr: 0.3860 <<<
Epoch [1/20], Step 8000, Train Loss: 0.7768, Val Avg Corr: 0.3703
Epoch [1/20], Step 8500, Train Loss: 0.7871, Val Avg Corr: 0.4354
  >>> New best validation model saved with Avg Corr: 0.4354 <<<
Epoch [1/20], Step 9000, Train Loss: 0.5836, Val Avg Corr: 0.3892
Epoch [1/20], Step 9500, Train Loss: 0.7424, Val Avg Corr: 0.4055
Epoch [1/20], Step 10000, Train Loss: 0.7173, Val Avg Corr: 0.4077
Epoch [1/20], Step 10500, Train Loss: 0.7130, Val Avg Corr: 0.4212
Epoch [1/20], Step 11000, Train Loss: 0.8040, Val Avg Corr: 0.4421
  >>> New best validation model saved with Avg Corr: 0.4421 <<<
Epoch [1/20], Step 11500, Train Loss: 0.9159, Val Avg Corr: 0.4710
  >>> New best validation model saved with Avg Corr: 0.4710 <<<
Epoch [1/20], Step 12000, Train Loss: 0.7831, Val Avg Corr: 0.5006
  >>> New best validation model saved with Avg Corr: 0.5006 <<<
Epoch [1/20], Step 12500, Train Loss: 0.6729, Val Avg Corr: 0.5238
  >>> New best validation model saved with Avg Corr: 0.5238 <<<
Epoch [1/20], Step 13000, Train Loss: 0.8272, Val Avg Corr: 0.5607
  >>> New best validation model saved with Avg Corr: 0.5607 <<<
Epoch [1/20], Step 13500, Train Loss: 0.6969, Val Avg Corr: 0.5587
Epoch [1/20], Step 14000, Train Loss: 0.8754, Val Avg Corr: 0.5746
  >>> New best validation model saved with Avg Corr: 0.5746 <<<
Epoch [1/20], Step 14500, Train Loss: 0.6341, Val Avg Corr: 0.6019
  >>> New best validation model saved with Avg Corr: 0.6019 <<<
Epoch [1/20], Step 15000, Train Loss: 0.6725, Val Avg Corr: 0.5872
Epoch [1/20], Step 15500, Train Loss: 0.6801, Val Avg Corr: 0.6006
Epoch [1/20], Step 16000, Train Loss: 0.4813, Val Avg Corr: 0.6084
  >>> New best validation model saved with Avg Corr: 0.6084 <<<
Epoch [1/20], Step 16500, Train Loss: 0.7209, Val Avg Corr: 0.6252
  >>> New best validation model saved with Avg Corr: 0.6252 <<<
Epoch [1/20], Step 17000, Train Loss: 0.6332, Val Avg Corr: 0.6178
Epoch [1/20], Step 17500, Train Loss: 0.7309, Val Avg Corr: 0.6181
Epoch [1/20], Step 18000, Train Loss: 0.6675, Val Avg Corr: 0.6327
  >>> New best validation model saved with Avg Corr: 0.6327 <<<
Epoch [1/20], Step 18500, Train Loss: 0.5401, Val Avg Corr: 0.6504
  >>> New best validation model saved with Avg Corr: 0.6504 <<<
Epoch [1/20], Step 19000, Train Loss: 0.7549, Val Avg Corr: 0.6424
Epoch [1/20], Step 19500, Train Loss: 0.4540, Val Avg Corr: 0.6519
  >>> New best validation model saved with Avg Corr: 0.6519 <<<
Epoch [1/20], Step 20000, Train Loss: 0.5600, Val Avg Corr: 0.6542
  >>> New best validation model saved with Avg Corr: 0.6542 <<<
Epoch [1/20], Step 20500, Train Loss: 0.5453, Val Avg Corr: 0.6568
  >>> New best validation model saved with Avg Corr: 0.6568 <<<
Trial change detected: 720 -> 722, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.5738, Val Avg Corr: 0.6588
  >>> New best validation model saved with Avg Corr: 0.6588 <<<
Epoch [1/20], Step 21500, Train Loss: 0.5006, Val Avg Corr: 0.6705
  >>> New best validation model saved with Avg Corr: 0.6705 <<<
Epoch [1/20], Step 22000, Train Loss: 0.5083, Val Avg Corr: 0.6665
Epoch [1/20], Step 22500, Train Loss: 0.5995, Val Avg Corr: 0.6718
  >>> New best validation model saved with Avg Corr: 0.6718 <<<
Epoch [1/20], Step 23000, Train Loss: 0.6706, Val Avg Corr: 0.6685
Epoch [1/20], Step 23500, Train Loss: 0.4665, Val Avg Corr: 0.6727
  >>> New best validation model saved with Avg Corr: 0.6727 <<<
Epoch [1/20], Step 24000, Train Loss: 0.5185, Val Avg Corr: 0.6816
  >>> New best validation model saved with Avg Corr: 0.6816 <<<
Epoch [1/20], Step 24500, Train Loss: 0.5787, Val Avg Corr: 0.6880
  >>> New best validation model saved with Avg Corr: 0.6880 <<<
Epoch [1/20], Step 25000, Train Loss: 0.5663, Val Avg Corr: 0.6918
  >>> New best validation model saved with Avg Corr: 0.6918 <<<
Epoch [1/20], Step 25500, Train Loss: 0.5517, Val Avg Corr: 0.7000
  >>> New best validation model saved with Avg Corr: 0.7000 <<<
Epoch [1/20], Step 26000, Train Loss: 0.4877, Val Avg Corr: 0.6923
Epoch [1/20], Step 26500, Train Loss: 0.4268, Val Avg Corr: 0.7025
  >>> New best validation model saved with Avg Corr: 0.7025 <<<
Epoch [1/20], Step 27000, Train Loss: 0.4554, Val Avg Corr: 0.6968
Epoch [1/20], Step 27500, Train Loss: 0.3931, Val Avg Corr: 0.7110
  >>> New best validation model saved with Avg Corr: 0.7110 <<<
Epoch [1/20], Step 28000, Train Loss: 0.5203, Val Avg Corr: 0.6999
Epoch [1/20], Step 28500, Train Loss: 0.5527, Val Avg Corr: 0.7117
  >>> New best validation model saved with Avg Corr: 0.7117 <<<
Epoch [1/20], Step 29000, Train Loss: 0.3803, Val Avg Corr: 0.7142
  >>> New best validation model saved with Avg Corr: 0.7142 <<<
Epoch [1/20], Step 29500, Train Loss: 0.4315, Val Avg Corr: 0.7176
  >>> New best validation model saved with Avg Corr: 0.7176 <<<
Epoch [1/20], Step 30000, Train Loss: 0.4867, Val Avg Corr: 0.7150
Epoch [1/20], Step 30500, Train Loss: 0.4889, Val Avg Corr: 0.7314
  >>> New best validation model saved with Avg Corr: 0.7314 <<<
Epoch [1/20], Step 31000, Train Loss: 0.4862, Val Avg Corr: 0.7261
Epoch [1/20], Step 31500, Train Loss: 0.4165, Val Avg Corr: 0.7214
Epoch [1/20], Step 32000, Train Loss: 0.5226, Val Avg Corr: 0.7293
Epoch [1/20], Step 32500, Train Loss: 0.4204, Val Avg Corr: 0.7269
Epoch [1/20], Step 33000, Train Loss: 0.4243, Val Avg Corr: 0.7308
Epoch [1/20], Step 33500, Train Loss: 0.5234, Val Avg Corr: 0.7266
Epoch [1/20], Step 34000, Train Loss: 0.4315, Val Avg Corr: 0.7331
  >>> New best validation model saved with Avg Corr: 0.7331 <<<
Epoch [1/20], Step 34500, Train Loss: 0.3843, Val Avg Corr: 0.7324
Epoch [1/20], Step 35000, Train Loss: 0.3534, Val Avg Corr: 0.7348
  >>> New best validation model saved with Avg Corr: 0.7348 <<<
Epoch [1/20], Step 35500, Train Loss: 0.3732, Val Avg Corr: 0.7340
Epoch [1/20], Step 36000, Train Loss: 0.3378, Val Avg Corr: 0.7373
  >>> New best validation model saved with Avg Corr: 0.7373 <<<
Epoch [1/20], Step 36500, Train Loss: 0.4447, Val Avg Corr: 0.7352
Epoch [1/20], Step 37000, Train Loss: 0.5436, Val Avg Corr: 0.7357
Epoch [1/20], Step 37500, Train Loss: 0.5432, Val Avg Corr: 0.7380
  >>> New best validation model saved with Avg Corr: 0.7380 <<<
Epoch [1/20], Step 38000, Train Loss: 0.4322, Val Avg Corr: 0.7427
  >>> New best validation model saved with Avg Corr: 0.7427 <<<
Epoch [1/20], Step 38500, Train Loss: 0.5240, Val Avg Corr: 0.7394
Epoch [1/20], Step 39000, Train Loss: 0.4187, Val Avg Corr: 0.7468
  >>> New best validation model saved with Avg Corr: 0.7468 <<<
Epoch [1/20], Step 39500, Train Loss: 0.4130, Val Avg Corr: 0.7477
  >>> New best validation model saved with Avg Corr: 0.7477 <<<
Epoch [1/20], Step 40000, Train Loss: 0.5426, Val Avg Corr: 0.7566
  >>> New best validation model saved with Avg Corr: 0.7566 <<<
Epoch [1/20], Step 40500, Train Loss: 0.5261, Val Avg Corr: 0.7503
Epoch [1/20], Step 41000, Train Loss: 0.3989, Val Avg Corr: 0.7489
Trial change detected: 1439 -> 1441, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.3250, Val Avg Corr: 0.7550
Epoch [1/20], Step 42000, Train Loss: 0.4052, Val Avg Corr: 0.7546
Epoch [1/20], Step 42500, Train Loss: 0.4320, Val Avg Corr: 0.7533
Epoch [1/20], Step 43000, Train Loss: 0.5265, Val Avg Corr: 0.7555
Epoch [1/20], Step 43500, Train Loss: 0.3461, Val Avg Corr: 0.7530
Epoch [1/20], Step 44000, Train Loss: 0.4300, Val Avg Corr: 0.7596
  >>> New best validation model saved with Avg Corr: 0.7596 <<<
Epoch [1/20], Step 44500, Train Loss: 0.4116, Val Avg Corr: 0.7520
Epoch [1/20], Step 45000, Train Loss: 0.4978, Val Avg Corr: 0.7586
Epoch [1/20], Step 45500, Train Loss: 0.3892, Val Avg Corr: 0.7565
Epoch [1/20], Step 46000, Train Loss: 0.3577, Val Avg Corr: 0.7579
Epoch [1/20], Step 46500, Train Loss: 0.4178, Val Avg Corr: 0.7645
  >>> New best validation model saved with Avg Corr: 0.7645 <<<
Epoch [1/20], Step 47000, Train Loss: 0.3435, Val Avg Corr: 0.7677
  >>> New best validation model saved with Avg Corr: 0.7677 <<<
Epoch [1/20], Step 47500, Train Loss: 0.4534, Val Avg Corr: 0.7639
Epoch [1/20], Step 48000, Train Loss: 0.2880, Val Avg Corr: 0.7653
Epoch [1/20], Step 48500, Train Loss: 0.5409, Val Avg Corr: 0.7668
Epoch [1/20], Step 49000, Train Loss: 0.4899, Val Avg Corr: 0.7687
  >>> New best validation model saved with Avg Corr: 0.7687 <<<
Epoch [1/20], Step 49500, Train Loss: 0.4939, Val Avg Corr: 0.7648
Epoch [1/20], Step 50000, Train Loss: 0.4681, Val Avg Corr: 0.7718
  >>> New best validation model saved with Avg Corr: 0.7718 <<<
Epoch [1/20], Step 50500, Train Loss: 0.3200, Val Avg Corr: 0.7677
Epoch [1/20], Step 51000, Train Loss: 0.4318, Val Avg Corr: 0.7692
Epoch [1/20], Step 51500, Train Loss: 0.3465, Val Avg Corr: 0.7675
Epoch [1/20], Step 52000, Train Loss: 0.3895, Val Avg Corr: 0.7670
Epoch [1/20], Step 52500, Train Loss: 0.4325, Val Avg Corr: 0.7703
Epoch [1/20], Step 53000, Train Loss: 0.4734, Val Avg Corr: 0.7755
  >>> New best validation model saved with Avg Corr: 0.7755 <<<
Epoch [1/20], Step 53500, Train Loss: 0.4561, Val Avg Corr: 0.7699
Epoch [1/20], Step 54000, Train Loss: 0.4212, Val Avg Corr: 0.7743
Epoch [1/20], Step 54500, Train Loss: 0.4819, Val Avg Corr: 0.7726
Epoch [1/20], Step 55000, Train Loss: 0.4670, Val Avg Corr: 0.7785
  >>> New best validation model saved with Avg Corr: 0.7785 <<<
Epoch [1/20], Step 55500, Train Loss: 0.3935, Val Avg Corr: 0.7739
Epoch [1/20], Step 56000, Train Loss: 0.3962, Val Avg Corr: 0.7827
  >>> New best validation model saved with Avg Corr: 0.7827 <<<
Epoch [1/20], Step 56500, Train Loss: 0.4019, Val Avg Corr: 0.7774
Epoch [1/20], Step 57000, Train Loss: 0.4749, Val Avg Corr: 0.7858
  >>> New best validation model saved with Avg Corr: 0.7858 <<<
Epoch [1/20], Step 57500, Train Loss: 0.4258, Val Avg Corr: 0.7859
  >>> New best validation model saved with Avg Corr: 0.7859 <<<
Epoch [1/20], Step 58000, Train Loss: 0.3626, Val Avg Corr: 0.7786
Epoch [1/20], Step 58500, Train Loss: 0.4316, Val Avg Corr: 0.7835
Epoch [1/20], Step 59000, Train Loss: 0.3522, Val Avg Corr: 0.7750
Epoch [1/20], Step 59500, Train Loss: 0.4007, Val Avg Corr: 0.7877
  >>> New best validation model saved with Avg Corr: 0.7877 <<<
Epoch [1/20], Step 60000, Train Loss: 0.3338, Val Avg Corr: 0.7813
Epoch [1/20], Step 60500, Train Loss: 0.4288, Val Avg Corr: 0.7797
Epoch [1/20], Step 61000, Train Loss: 0.4137, Val Avg Corr: 0.7890
  >>> New best validation model saved with Avg Corr: 0.7890 <<<
Epoch [1/20], Step 61500, Train Loss: 0.4006, Val Avg Corr: 0.7836
Trial change detected: 2149 -> 2152, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3071, Val Avg Corr: 0.7845
Epoch [1/20], Step 62500, Train Loss: 0.3487, Val Avg Corr: 0.7904
  >>> New best validation model saved with Avg Corr: 0.7904 <<<
Epoch [1/20], Step 63000, Train Loss: 0.3353, Val Avg Corr: 0.7926
  >>> New best validation model saved with Avg Corr: 0.7926 <<<
Epoch [1/20], Step 63500, Train Loss: 0.4174, Val Avg Corr: 0.7933
  >>> New best validation model saved with Avg Corr: 0.7933 <<<
Epoch [1/20], Step 64000, Train Loss: 0.4036, Val Avg Corr: 0.7918
Epoch [1/20], Step 64500, Train Loss: 0.3656, Val Avg Corr: 0.7896
Epoch [1/20], Step 65000, Train Loss: 0.4192, Val Avg Corr: 0.7930
Epoch [1/20], Step 65500, Train Loss: 0.4112, Val Avg Corr: 0.7930
Epoch [2/20], Step 500, Train Loss: 0.4104, Val Avg Corr: 0.7934
  >>> New best validation model saved with Avg Corr: 0.7934 <<<
Epoch [2/20], Step 1000, Train Loss: 0.3861, Val Avg Corr: 0.7934
Epoch [2/20], Step 1500, Train Loss: 0.4865, Val Avg Corr: 0.7906
Epoch [2/20], Step 2000, Train Loss: 0.3827, Val Avg Corr: 0.7923
Epoch [2/20], Step 2500, Train Loss: 0.3304, Val Avg Corr: 0.7947
  >>> New best validation model saved with Avg Corr: 0.7947 <<<
Epoch [2/20], Step 3000, Train Loss: 0.3382, Val Avg Corr: 0.7957
  >>> New best validation model saved with Avg Corr: 0.7957 <<<
Epoch [2/20], Step 3500, Train Loss: 0.4125, Val Avg Corr: 0.7895
Epoch [2/20], Step 4000, Train Loss: 0.2985, Val Avg Corr: 0.7949
Epoch [2/20], Step 4500, Train Loss: 0.3550, Val Avg Corr: 0.7929
Epoch [2/20], Step 5000, Train Loss: 0.5588, Val Avg Corr: 0.7929
Epoch [2/20], Step 5500, Train Loss: 0.4008, Val Avg Corr: 0.7913
Epoch [2/20], Step 6000, Train Loss: 0.3554, Val Avg Corr: 0.7878
Epoch [2/20], Step 6500, Train Loss: 0.3184, Val Avg Corr: 0.7993
  >>> New best validation model saved with Avg Corr: 0.7993 <<<
Epoch [2/20], Step 7000, Train Loss: 0.3522, Val Avg Corr: 0.8012
  >>> New best validation model saved with Avg Corr: 0.8012 <<<
Epoch [2/20], Step 7500, Train Loss: 0.4170, Val Avg Corr: 0.7929
Epoch [2/20], Step 8000, Train Loss: 0.3374, Val Avg Corr: 0.8000
Epoch [2/20], Step 8500, Train Loss: 0.3529, Val Avg Corr: 0.7988
Epoch [2/20], Step 9000, Train Loss: 0.2714, Val Avg Corr: 0.7929
Epoch [2/20], Step 9500, Train Loss: 0.3523, Val Avg Corr: 0.7976
Epoch [2/20], Step 10000, Train Loss: 0.2873, Val Avg Corr: 0.8022
  >>> New best validation model saved with Avg Corr: 0.8022 <<<
Epoch [2/20], Step 10500, Train Loss: 0.3896, Val Avg Corr: 0.7947
Epoch [2/20], Step 11000, Train Loss: 0.3391, Val Avg Corr: 0.8013
Epoch [2/20], Step 11500, Train Loss: 0.4035, Val Avg Corr: 0.7937
Epoch [2/20], Step 12000, Train Loss: 0.3434, Val Avg Corr: 0.7957
Epoch [2/20], Step 12500, Train Loss: 0.3675, Val Avg Corr: 0.7948
Epoch [2/20], Step 13000, Train Loss: 0.3591, Val Avg Corr: 0.7987
Epoch [2/20], Step 13500, Train Loss: 0.3582, Val Avg Corr: 0.7978
Epoch [2/20], Step 14000, Train Loss: 0.4579, Val Avg Corr: 0.8034
  >>> New best validation model saved with Avg Corr: 0.8034 <<<
Epoch [2/20], Step 14500, Train Loss: 0.2940, Val Avg Corr: 0.8029
Epoch [2/20], Step 15000, Train Loss: 0.3235, Val Avg Corr: 0.7958
Epoch [2/20], Step 15500, Train Loss: 0.4391, Val Avg Corr: 0.8039
  >>> New best validation model saved with Avg Corr: 0.8039 <<<
Epoch [2/20], Step 16000, Train Loss: 0.2910, Val Avg Corr: 0.7990
Epoch [2/20], Step 16500, Train Loss: 0.4198, Val Avg Corr: 0.7996
Epoch [2/20], Step 17000, Train Loss: 0.3936, Val Avg Corr: 0.8038
Epoch [2/20], Step 17500, Train Loss: 0.4035, Val Avg Corr: 0.8005
Epoch [2/20], Step 18000, Train Loss: 0.4149, Val Avg Corr: 0.8040
  >>> New best validation model saved with Avg Corr: 0.8040 <<<
Epoch [2/20], Step 18500, Train Loss: 0.3447, Val Avg Corr: 0.8013
Epoch [2/20], Step 19000, Train Loss: 0.4762, Val Avg Corr: 0.8054
  >>> New best validation model saved with Avg Corr: 0.8054 <<<
Epoch [2/20], Step 19500, Train Loss: 0.3092, Val Avg Corr: 0.8004
Epoch [2/20], Step 20000, Train Loss: 0.3512, Val Avg Corr: 0.8004
Epoch [2/20], Step 20500, Train Loss: 0.3489, Val Avg Corr: 0.8013
Trial change detected: 720 -> 722, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.3082, Val Avg Corr: 0.8014
Epoch [2/20], Step 21500, Train Loss: 0.3223, Val Avg Corr: 0.8027
Epoch [2/20], Step 22000, Train Loss: 0.3797, Val Avg Corr: 0.8056
  >>> New best validation model saved with Avg Corr: 0.8056 <<<
Epoch [2/20], Step 22500, Train Loss: 0.4595, Val Avg Corr: 0.7969
Epoch [2/20], Step 23000, Train Loss: 0.4181, Val Avg Corr: 0.8022
Epoch [2/20], Step 23500, Train Loss: 0.3245, Val Avg Corr: 0.7958
Epoch [2/20], Step 24000, Train Loss: 0.4042, Val Avg Corr: 0.8027
Epoch [2/20], Step 24500, Train Loss: 0.4135, Val Avg Corr: 0.7996
Epoch [2/20], Step 25000, Train Loss: 0.3449, Val Avg Corr: 0.8009
Epoch [2/20], Step 25500, Train Loss: 0.3076, Val Avg Corr: 0.8014
Epoch [2/20], Step 26000, Train Loss: 0.2931, Val Avg Corr: 0.8003
Epoch [2/20], Step 26500, Train Loss: 0.2892, Val Avg Corr: 0.8036
Epoch [2/20], Step 27000, Train Loss: 0.3765, Val Avg Corr: 0.8019
Epoch [2/20], Step 27500, Train Loss: 0.2764, Val Avg Corr: 0.8050
Epoch [2/20], Step 28000, Train Loss: 0.3730, Val Avg Corr: 0.7990
Epoch [2/20], Step 28500, Train Loss: 0.3869, Val Avg Corr: 0.8018
Epoch [2/20], Step 29000, Train Loss: 0.2754, Val Avg Corr: 0.8028
Epoch [2/20], Step 29500, Train Loss: 0.3643, Val Avg Corr: 0.8079
  >>> New best validation model saved with Avg Corr: 0.8079 <<<
Epoch [2/20], Step 30000, Train Loss: 0.3232, Val Avg Corr: 0.8027
Epoch [2/20], Step 30500, Train Loss: 0.3828, Val Avg Corr: 0.8044
Epoch [2/20], Step 31000, Train Loss: 0.3523, Val Avg Corr: 0.8009
Epoch [2/20], Step 31500, Train Loss: 0.3029, Val Avg Corr: 0.8035
Epoch [2/20], Step 32000, Train Loss: 0.4217, Val Avg Corr: 0.8026
Epoch [2/20], Step 32500, Train Loss: 0.3253, Val Avg Corr: 0.8034
Epoch [2/20], Step 33000, Train Loss: 0.3187, Val Avg Corr: 0.8091
  >>> New best validation model saved with Avg Corr: 0.8091 <<<
Epoch [2/20], Step 33500, Train Loss: 0.4054, Val Avg Corr: 0.8075
Epoch [2/20], Step 34000, Train Loss: 0.3260, Val Avg Corr: 0.8072
Epoch [2/20], Step 34500, Train Loss: 0.2950, Val Avg Corr: 0.8012
Epoch [2/20], Step 35000, Train Loss: 0.2698, Val Avg Corr: 0.8095
  >>> New best validation model saved with Avg Corr: 0.8095 <<<
Epoch [2/20], Step 35500, Train Loss: 0.3247, Val Avg Corr: 0.8063
Epoch [2/20], Step 36000, Train Loss: 0.2404, Val Avg Corr: 0.8007
Epoch [2/20], Step 36500, Train Loss: 0.3121, Val Avg Corr: 0.8051
Epoch [2/20], Step 37000, Train Loss: 0.4333, Val Avg Corr: 0.8028
Epoch [2/20], Step 37500, Train Loss: 0.4064, Val Avg Corr: 0.8045
Epoch [2/20], Step 38000, Train Loss: 0.3558, Val Avg Corr: 0.8072
Epoch [2/20], Step 38500, Train Loss: 0.4148, Val Avg Corr: 0.8017
Epoch [2/20], Step 39000, Train Loss: 0.3211, Val Avg Corr: 0.8059
Epoch [2/20], Step 39500, Train Loss: 0.2827, Val Avg Corr: 0.8078
Epoch [2/20], Step 40000, Train Loss: 0.4567, Val Avg Corr: 0.8023
Epoch [2/20], Step 40500, Train Loss: 0.3955, Val Avg Corr: 0.8014
Epoch [2/20], Step 41000, Train Loss: 0.3116, Val Avg Corr: 0.7998
Trial change detected: 1439 -> 1441, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.2454, Val Avg Corr: 0.7969
Epoch [2/20], Step 42000, Train Loss: 0.3162, Val Avg Corr: 0.8054
Epoch [2/20], Step 42500, Train Loss: 0.3622, Val Avg Corr: 0.8026
Epoch [2/20], Step 43000, Train Loss: 0.3656, Val Avg Corr: 0.8019
Epoch [2/20], Step 43500, Train Loss: 0.2732, Val Avg Corr: 0.8029
Epoch [2/20], Step 44000, Train Loss: 0.3613, Val Avg Corr: 0.8004
Epoch [2/20], Step 44500, Train Loss: 0.3596, Val Avg Corr: 0.8075
Epoch [2/20], Step 45000, Train Loss: 0.3893, Val Avg Corr: 0.8151
  >>> New best validation model saved with Avg Corr: 0.8151 <<<
Epoch [2/20], Step 45500, Train Loss: 0.3499, Val Avg Corr: 0.8056
Epoch [2/20], Step 46000, Train Loss: 0.3461, Val Avg Corr: 0.8101
Epoch [2/20], Step 46500, Train Loss: 0.3372, Val Avg Corr: 0.8041
Epoch [2/20], Step 47000, Train Loss: 0.2845, Val Avg Corr: 0.8020
Epoch [2/20], Step 47500, Train Loss: 0.3582, Val Avg Corr: 0.8098
Epoch [2/20], Step 48000, Train Loss: 0.2451, Val Avg Corr: 0.8040
Epoch [2/20], Step 48500, Train Loss: 0.4591, Val Avg Corr: 0.8040
Epoch [2/20], Step 49000, Train Loss: 0.3689, Val Avg Corr: 0.8093
Epoch [2/20], Step 49500, Train Loss: 0.4071, Val Avg Corr: 0.8029
Epoch [2/20], Step 50000, Train Loss: 0.3889, Val Avg Corr: 0.8039
Epoch [2/20], Step 50500, Train Loss: 0.2769, Val Avg Corr: 0.8092
Epoch [2/20], Step 51000, Train Loss: 0.3376, Val Avg Corr: 0.8050
Epoch [2/20], Step 51500, Train Loss: 0.2654, Val Avg Corr: 0.8066
Epoch [2/20], Step 52000, Train Loss: 0.3357, Val Avg Corr: 0.8096
Epoch [2/20], Step 52500, Train Loss: 0.4149, Val Avg Corr: 0.8136
Epoch [2/20], Step 53000, Train Loss: 0.3776, Val Avg Corr: 0.8074
Epoch [2/20], Step 53500, Train Loss: 0.3813, Val Avg Corr: 0.8107
Epoch [2/20], Step 54000, Train Loss: 0.3864, Val Avg Corr: 0.8121
Epoch [2/20], Step 54500, Train Loss: 0.3779, Val Avg Corr: 0.8098
Epoch [2/20], Step 55000, Train Loss: 0.3984, Val Avg Corr: 0.8072
Epoch [2/20], Step 55500, Train Loss: 0.3223, Val Avg Corr: 0.8128
Epoch [2/20], Step 56000, Train Loss: 0.3362, Val Avg Corr: 0.8071
Epoch [2/20], Step 56500, Train Loss: 0.3672, Val Avg Corr: 0.8120
Epoch [2/20], Step 57000, Train Loss: 0.3867, Val Avg Corr: 0.8154
  >>> New best validation model saved with Avg Corr: 0.8154 <<<
Epoch [2/20], Step 57500, Train Loss: 0.3480, Val Avg Corr: 0.8107
Epoch [2/20], Step 58000, Train Loss: 0.3142, Val Avg Corr: 0.8089
Epoch [2/20], Step 58500, Train Loss: 0.3841, Val Avg Corr: 0.8119
Epoch [2/20], Step 59000, Train Loss: 0.2832, Val Avg Corr: 0.8102
Epoch [2/20], Step 59500, Train Loss: 0.3319, Val Avg Corr: 0.8091
Epoch [2/20], Step 60000, Train Loss: 0.2819, Val Avg Corr: 0.8063
Epoch [2/20], Step 60500, Train Loss: 0.3507, Val Avg Corr: 0.8115
Epoch [2/20], Step 61000, Train Loss: 0.3325, Val Avg Corr: 0.8118
Epoch [2/20], Step 61500, Train Loss: 0.3336, Val Avg Corr: 0.8127
Trial change detected: 2149 -> 2152, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.2856, Val Avg Corr: 0.8116
Epoch [2/20], Step 62500, Train Loss: 0.3283, Val Avg Corr: 0.8056
Epoch [2/20], Step 63000, Train Loss: 0.2930, Val Avg Corr: 0.8132
Epoch [2/20], Step 63500, Train Loss: 0.3367, Val Avg Corr: 0.8135
Epoch [2/20], Step 64000, Train Loss: 0.3971, Val Avg Corr: 0.8126
Epoch [2/20], Step 64500, Train Loss: 0.3041, Val Avg Corr: 0.8123
Epoch [2/20], Step 65000, Train Loss: 0.3591, Val Avg Corr: 0.8138
Epoch [2/20], Step 65500, Train Loss: 0.3481, Val Avg Corr: 0.8109
Epoch [3/20], Step 500, Train Loss: 0.3432, Val Avg Corr: 0.8184
  >>> New best validation model saved with Avg Corr: 0.8184 <<<
Epoch [3/20], Step 1000, Train Loss: 0.3225, Val Avg Corr: 0.8181
Epoch [3/20], Step 1500, Train Loss: 0.3988, Val Avg Corr: 0.8106
Epoch [3/20], Step 2000, Train Loss: 0.3261, Val Avg Corr: 0.8098
Epoch [3/20], Step 2500, Train Loss: 0.2704, Val Avg Corr: 0.8156
Epoch [3/20], Step 3000, Train Loss: 0.3074, Val Avg Corr: 0.8144
Epoch [3/20], Step 3500, Train Loss: 0.3439, Val Avg Corr: 0.8208
  >>> New best validation model saved with Avg Corr: 0.8208 <<<
Epoch [3/20], Step 4000, Train Loss: 0.2996, Val Avg Corr: 0.8110
Epoch [3/20], Step 4500, Train Loss: 0.3077, Val Avg Corr: 0.8122
Epoch [3/20], Step 5000, Train Loss: 0.5109, Val Avg Corr: 0.8071
Epoch [3/20], Step 5500, Train Loss: 0.3467, Val Avg Corr: 0.8113
Epoch [3/20], Step 6000, Train Loss: 0.3120, Val Avg Corr: 0.8136
Epoch [3/20], Step 6500, Train Loss: 0.2936, Val Avg Corr: 0.8161
Epoch [3/20], Step 7000, Train Loss: 0.3048, Val Avg Corr: 0.8153
Epoch [3/20], Step 7500, Train Loss: 0.3552, Val Avg Corr: 0.8113
Epoch [3/20], Step 8000, Train Loss: 0.3071, Val Avg Corr: 0.8087
Epoch [3/20], Step 8500, Train Loss: 0.2946, Val Avg Corr: 0.8184
Epoch [3/20], Step 9000, Train Loss: 0.2304, Val Avg Corr: 0.8179
Epoch [3/20], Step 9500, Train Loss: 0.3085, Val Avg Corr: 0.8119
Epoch [3/20], Step 10000, Train Loss: 0.2666, Val Avg Corr: 0.8116
Epoch [3/20], Step 10500, Train Loss: 0.3505, Val Avg Corr: 0.8195
Epoch [3/20], Step 11000, Train Loss: 0.2854, Val Avg Corr: 0.8075
Epoch [3/20], Step 11500, Train Loss: 0.3622, Val Avg Corr: 0.8120
Epoch [3/20], Step 12000, Train Loss: 0.3155, Val Avg Corr: 0.8125
Epoch [3/20], Step 12500, Train Loss: 0.3390, Val Avg Corr: 0.8089
Epoch [3/20], Step 13000, Train Loss: 0.3220, Val Avg Corr: 0.8153
Epoch [3/20], Step 13500, Train Loss: 0.3217, Val Avg Corr: 0.8128
Epoch [3/20], Step 14000, Train Loss: 0.4120, Val Avg Corr: 0.8116
Epoch [3/20], Step 14500, Train Loss: 0.2867, Val Avg Corr: 0.8133
Epoch [3/20], Step 15000, Train Loss: 0.2967, Val Avg Corr: 0.8137
Epoch [3/20], Step 15500, Train Loss: 0.3701, Val Avg Corr: 0.8163
Epoch [3/20], Step 16000, Train Loss: 0.2692, Val Avg Corr: 0.8125
Epoch [3/20], Step 16500, Train Loss: 0.4008, Val Avg Corr: 0.8115
Epoch [3/20], Step 17000, Train Loss: 0.3565, Val Avg Corr: 0.8188
Epoch [3/20], Step 17500, Train Loss: 0.3641, Val Avg Corr: 0.8139
Epoch [3/20], Step 18000, Train Loss: 0.3818, Val Avg Corr: 0.8159
Epoch [3/20], Step 18500, Train Loss: 0.3193, Val Avg Corr: 0.8157
Epoch [3/20], Step 19000, Train Loss: 0.4136, Val Avg Corr: 0.8212
  >>> New best validation model saved with Avg Corr: 0.8212 <<<
Epoch [3/20], Step 19500, Train Loss: 0.2790, Val Avg Corr: 0.8134
Epoch [3/20], Step 20000, Train Loss: 0.3148, Val Avg Corr: 0.8199
Epoch [3/20], Step 20500, Train Loss: 0.2928, Val Avg Corr: 0.8127
Trial change detected: 720 -> 722, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.2897, Val Avg Corr: 0.8156
Epoch [3/20], Step 21500, Train Loss: 0.2995, Val Avg Corr: 0.8150
Epoch [3/20], Step 22000, Train Loss: 0.3220, Val Avg Corr: 0.8168
Epoch [3/20], Step 22500, Train Loss: 0.4391, Val Avg Corr: 0.8120
Epoch [3/20], Step 23000, Train Loss: 0.3442, Val Avg Corr: 0.8144
Epoch [3/20], Step 23500, Train Loss: 0.3174, Val Avg Corr: 0.8146
Epoch [3/20], Step 24000, Train Loss: 0.3579, Val Avg Corr: 0.8187
Epoch [3/20], Step 24500, Train Loss: 0.3770, Val Avg Corr: 0.8150
Epoch [3/20], Step 25000, Train Loss: 0.3253, Val Avg Corr: 0.8110
Epoch [3/20], Step 25500, Train Loss: 0.2866, Val Avg Corr: 0.8184
Epoch [3/20], Step 26000, Train Loss: 0.2675, Val Avg Corr: 0.8164
Epoch [3/20], Step 26500, Train Loss: 0.2648, Val Avg Corr: 0.8180
Epoch [3/20], Step 27000, Train Loss: 0.3288, Val Avg Corr: 0.8202
Epoch [3/20], Step 27500, Train Loss: 0.2625, Val Avg Corr: 0.8163
Epoch [3/20], Step 28000, Train Loss: 0.3133, Val Avg Corr: 0.8192
Epoch [3/20], Step 28500, Train Loss: 0.3241, Val Avg Corr: 0.8113
Epoch [3/20], Step 29000, Train Loss: 0.2554, Val Avg Corr: 0.8177
Epoch [3/20], Step 29500, Train Loss: 0.3241, Val Avg Corr: 0.8170
Epoch [3/20], Step 30000, Train Loss: 0.3160, Val Avg Corr: 0.8207
Epoch [3/20], Step 30500, Train Loss: 0.3683, Val Avg Corr: 0.8197
Epoch [3/20], Step 31000, Train Loss: 0.3074, Val Avg Corr: 0.8184
Epoch [3/20], Step 31500, Train Loss: 0.2957, Val Avg Corr: 0.8151
Epoch [3/20], Step 32000, Train Loss: 0.3899, Val Avg Corr: 0.8158
Epoch [3/20], Step 32500, Train Loss: 0.3223, Val Avg Corr: 0.8201
Epoch [3/20], Step 33000, Train Loss: 0.3038, Val Avg Corr: 0.8243
  >>> New best validation model saved with Avg Corr: 0.8243 <<<
Epoch [3/20], Step 33500, Train Loss: 0.3828, Val Avg Corr: 0.8185
Epoch [3/20], Step 34000, Train Loss: 0.2946, Val Avg Corr: 0.8189
Epoch [3/20], Step 34500, Train Loss: 0.2637, Val Avg Corr: 0.8165
Epoch [3/20], Step 35000, Train Loss: 0.2380, Val Avg Corr: 0.8208
Epoch [3/20], Step 35500, Train Loss: 0.2894, Val Avg Corr: 0.8157
Epoch [3/20], Step 36000, Train Loss: 0.2073, Val Avg Corr: 0.8151
Epoch [3/20], Step 36500, Train Loss: 0.2509, Val Avg Corr: 0.8200
Epoch [3/20], Step 37000, Train Loss: 0.3886, Val Avg Corr: 0.8229
Epoch [3/20], Step 37500, Train Loss: 0.3744, Val Avg Corr: 0.8200
Epoch [3/20], Step 38000, Train Loss: 0.3593, Val Avg Corr: 0.8211
Epoch [3/20], Step 38500, Train Loss: 0.3941, Val Avg Corr: 0.8157
Epoch [3/20], Step 39000, Train Loss: 0.2975, Val Avg Corr: 0.8210
Epoch [3/20], Step 39500, Train Loss: 0.2501, Val Avg Corr: 0.8188
Epoch [3/20], Step 40000, Train Loss: 0.4106, Val Avg Corr: 0.8116
Epoch [3/20], Step 40500, Train Loss: 0.3543, Val Avg Corr: 0.8165
Epoch [3/20], Step 41000, Train Loss: 0.2773, Val Avg Corr: 0.8156
Trial change detected: 1439 -> 1441, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.2360, Val Avg Corr: 0.8213
Epoch [3/20], Step 42000, Train Loss: 0.2965, Val Avg Corr: 0.8153
Epoch [3/20], Step 42500, Train Loss: 0.3463, Val Avg Corr: 0.8188
Epoch [3/20], Step 43000, Train Loss: 0.3287, Val Avg Corr: 0.8193
Epoch [3/20], Step 43500, Train Loss: 0.2560, Val Avg Corr: 0.8167
Epoch [3/20], Step 44000, Train Loss: 0.3243, Val Avg Corr: 0.8141
Epoch [3/20], Step 44500, Train Loss: 0.3415, Val Avg Corr: 0.8200
Epoch [3/20], Step 45000, Train Loss: 0.3640, Val Avg Corr: 0.8234
Epoch [3/20], Step 45500, Train Loss: 0.3358, Val Avg Corr: 0.8185
Epoch [3/20], Step 46000, Train Loss: 0.3303, Val Avg Corr: 0.8186
Epoch [3/20], Step 46500, Train Loss: 0.3060, Val Avg Corr: 0.8183
Epoch [3/20], Step 47000, Train Loss: 0.2502, Val Avg Corr: 0.8141
Epoch [3/20], Step 47500, Train Loss: 0.3343, Val Avg Corr: 0.8199
Epoch [3/20], Step 48000, Train Loss: 0.2296, Val Avg Corr: 0.8151
Epoch [3/20], Step 48500, Train Loss: 0.4151, Val Avg Corr: 0.8167
Epoch [3/20], Step 49000, Train Loss: 0.3610, Val Avg Corr: 0.8190
Epoch [3/20], Step 49500, Train Loss: 0.3688, Val Avg Corr: 0.8200
Epoch [3/20], Step 50000, Train Loss: 0.3584, Val Avg Corr: 0.8227
Epoch [3/20], Step 50500, Train Loss: 0.2722, Val Avg Corr: 0.8182
Epoch [3/20], Step 51000, Train Loss: 0.3154, Val Avg Corr: 0.8183
Epoch [3/20], Step 51500, Train Loss: 0.2429, Val Avg Corr: 0.8162
Epoch [3/20], Step 52000, Train Loss: 0.3096, Val Avg Corr: 0.8186
Epoch [3/20], Step 52500, Train Loss: 0.3719, Val Avg Corr: 0.8221
Epoch [3/20], Step 53000, Train Loss: 0.3382, Val Avg Corr: 0.8213
Epoch [3/20], Step 53500, Train Loss: 0.3558, Val Avg Corr: 0.8213
Epoch [3/20], Step 54000, Train Loss: 0.3734, Val Avg Corr: 0.8214
Epoch [3/20], Step 54500, Train Loss: 0.3385, Val Avg Corr: 0.8205
Epoch [3/20], Step 55000, Train Loss: 0.3621, Val Avg Corr: 0.8214
Epoch [3/20], Step 55500, Train Loss: 0.2999, Val Avg Corr: 0.8131
Epoch [3/20], Step 56000, Train Loss: 0.2961, Val Avg Corr: 0.8154
Epoch [3/20], Step 56500, Train Loss: 0.3481, Val Avg Corr: 0.8165
Epoch [3/20], Step 57000, Train Loss: 0.3653, Val Avg Corr: 0.8251
  >>> New best validation model saved with Avg Corr: 0.8251 <<<
Epoch [3/20], Step 57500, Train Loss: 0.3289, Val Avg Corr: 0.8199
Epoch [3/20], Step 58000, Train Loss: 0.2881, Val Avg Corr: 0.8191
Epoch [3/20], Step 58500, Train Loss: 0.3459, Val Avg Corr: 0.8231
Epoch [3/20], Step 59000, Train Loss: 0.2657, Val Avg Corr: 0.8218
Epoch [3/20], Step 59500, Train Loss: 0.3166, Val Avg Corr: 0.8235
Epoch [3/20], Step 60000, Train Loss: 0.2350, Val Avg Corr: 0.8198
Epoch [3/20], Step 60500, Train Loss: 0.3176, Val Avg Corr: 0.8206
Epoch [3/20], Step 61000, Train Loss: 0.3142, Val Avg Corr: 0.8198
Epoch [3/20], Step 61500, Train Loss: 0.3116, Val Avg Corr: 0.8249
Trial change detected: 2149 -> 2152, resetting states
Epoch [3/20], Step 62000, Train Loss: 0.2619, Val Avg Corr: 0.8275
  >>> New best validation model saved with Avg Corr: 0.8275 <<<
Epoch [3/20], Step 62500, Train Loss: 0.3046, Val Avg Corr: 0.8260
Epoch [3/20], Step 63000, Train Loss: 0.2692, Val Avg Corr: 0.8214
Epoch [3/20], Step 63500, Train Loss: 0.3123, Val Avg Corr: 0.8277
  >>> New best validation model saved with Avg Corr: 0.8277 <<<
Epoch [3/20], Step 64000, Train Loss: 0.3642, Val Avg Corr: 0.8246
Epoch [3/20], Step 64500, Train Loss: 0.2953, Val Avg Corr: 0.8251
Epoch [3/20], Step 65000, Train Loss: 0.3273, Val Avg Corr: 0.8310
  >>> New best validation model saved with Avg Corr: 0.8310 <<<
Epoch [3/20], Step 65500, Train Loss: 0.3251, Val Avg Corr: 0.8273
Epoch [4/20], Step 500, Train Loss: 0.3117, Val Avg Corr: 0.8235
Epoch [4/20], Step 1000, Train Loss: 0.2959, Val Avg Corr: 0.8278
Epoch [4/20], Step 1500, Train Loss: 0.4000, Val Avg Corr: 0.8233
Epoch [4/20], Step 2000, Train Loss: 0.3038, Val Avg Corr: 0.8230
Epoch [4/20], Step 2500, Train Loss: 0.2443, Val Avg Corr: 0.8240
Epoch [4/20], Step 3000, Train Loss: 0.2865, Val Avg Corr: 0.8244
Epoch [4/20], Step 3500, Train Loss: 0.3191, Val Avg Corr: 0.8321
  >>> New best validation model saved with Avg Corr: 0.8321 <<<
Epoch [4/20], Step 4000, Train Loss: 0.2758, Val Avg Corr: 0.8219
Epoch [4/20], Step 4500, Train Loss: 0.3086, Val Avg Corr: 0.8254
Epoch [4/20], Step 5000, Train Loss: 0.5011, Val Avg Corr: 0.8262
Epoch [4/20], Step 5500, Train Loss: 0.3303, Val Avg Corr: 0.8219
Epoch [4/20], Step 6000, Train Loss: 0.2885, Val Avg Corr: 0.8229
Epoch [4/20], Step 6500, Train Loss: 0.2707, Val Avg Corr: 0.8259
Epoch [4/20], Step 7000, Train Loss: 0.2879, Val Avg Corr: 0.8235
Epoch [4/20], Step 7500, Train Loss: 0.3411, Val Avg Corr: 0.8244
Epoch [4/20], Step 8000, Train Loss: 0.2908, Val Avg Corr: 0.8266
Epoch [4/20], Step 8500, Train Loss: 0.2725, Val Avg Corr: 0.8242
Epoch [4/20], Step 9000, Train Loss: 0.2199, Val Avg Corr: 0.8282
Epoch [4/20], Step 9500, Train Loss: 0.2966, Val Avg Corr: 0.8267
Epoch [4/20], Step 10000, Train Loss: 0.2443, Val Avg Corr: 0.8210
Epoch [4/20], Step 10500, Train Loss: 0.3266, Val Avg Corr: 0.8211
Epoch [4/20], Step 11000, Train Loss: 0.2660, Val Avg Corr: 0.8248
Epoch [4/20], Step 11500, Train Loss: 0.3335, Val Avg Corr: 0.8262
Epoch [4/20], Step 12000, Train Loss: 0.2884, Val Avg Corr: 0.8240
Epoch [4/20], Step 12500, Train Loss: 0.3250, Val Avg Corr: 0.8186
Epoch [4/20], Step 13000, Train Loss: 0.2970, Val Avg Corr: 0.8190
Epoch [4/20], Step 13500, Train Loss: 0.2960, Val Avg Corr: 0.8238
Epoch [4/20], Step 14000, Train Loss: 0.3772, Val Avg Corr: 0.8225
Epoch [4/20], Step 14500, Train Loss: 0.2644, Val Avg Corr: 0.8218
Epoch [4/20], Step 15000, Train Loss: 0.2969, Val Avg Corr: 0.8194
Epoch [4/20], Step 15500, Train Loss: 0.3400, Val Avg Corr: 0.8180
Epoch [4/20], Step 16000, Train Loss: 0.2567, Val Avg Corr: 0.8198
Epoch [4/20], Step 16500, Train Loss: 0.3866, Val Avg Corr: 0.8277
Epoch [4/20], Step 17000, Train Loss: 0.3342, Val Avg Corr: 0.8267
Epoch [4/20], Step 17500, Train Loss: 0.3256, Val Avg Corr: 0.8190
Epoch [4/20], Step 18000, Train Loss: 0.3691, Val Avg Corr: 0.8246
Epoch [4/20], Step 18500, Train Loss: 0.3151, Val Avg Corr: 0.8263
Epoch [4/20], Step 19000, Train Loss: 0.3756, Val Avg Corr: 0.8227
Epoch [4/20], Step 19500, Train Loss: 0.2663, Val Avg Corr: 0.8284
Epoch [4/20], Step 20000, Train Loss: 0.2891, Val Avg Corr: 0.8266
Epoch [4/20], Step 20500, Train Loss: 0.2641, Val Avg Corr: 0.8224
Trial change detected: 720 -> 722, resetting states
Epoch [4/20], Step 21000, Train Loss: 0.2602, Val Avg Corr: 0.8233
Epoch [4/20], Step 21500, Train Loss: 0.2888, Val Avg Corr: 0.8219
Epoch [4/20], Step 22000, Train Loss: 0.3050, Val Avg Corr: 0.8244
Epoch [4/20], Step 22500, Train Loss: 0.4100, Val Avg Corr: 0.8175
Epoch [4/20], Step 23000, Train Loss: 0.3251, Val Avg Corr: 0.8226
Epoch [4/20], Step 23500, Train Loss: 0.2971, Val Avg Corr: 0.8270
Epoch [4/20], Step 24000, Train Loss: 0.3423, Val Avg Corr: 0.8276
Epoch [4/20], Step 24500, Train Loss: 0.3589, Val Avg Corr: 0.8246
Epoch [4/20], Step 25000, Train Loss: 0.3258, Val Avg Corr: 0.8269
Epoch [4/20], Step 25500, Train Loss: 0.2544, Val Avg Corr: 0.8253
Epoch [4/20], Step 26000, Train Loss: 0.2530, Val Avg Corr: 0.8260
Epoch [4/20], Step 26500, Train Loss: 0.2588, Val Avg Corr: 0.8228
Epoch [4/20], Step 27000, Train Loss: 0.3030, Val Avg Corr: 0.8279
Epoch [4/20], Step 27500, Train Loss: 0.2555, Val Avg Corr: 0.8301
Epoch [4/20], Step 28000, Train Loss: 0.3045, Val Avg Corr: 0.8267
Epoch [4/20], Step 28500, Train Loss: 0.2948, Val Avg Corr: 0.8270
Early stopping triggered after 28500 steps in epoch 4.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8321
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8449, Y=0.8180, Avg=0.8314

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 5) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.1452, Val Avg Corr: 0.1265
  >>> New best validation model saved with Avg Corr: 0.1265 <<<
Epoch [1/20], Step 1000, Train Loss: 1.2088, Val Avg Corr: 0.1695
  >>> New best validation model saved with Avg Corr: 0.1695 <<<
Epoch [1/20], Step 1500, Train Loss: 0.9905, Val Avg Corr: 0.1849
  >>> New best validation model saved with Avg Corr: 0.1849 <<<
Epoch [1/20], Step 2000, Train Loss: 1.0157, Val Avg Corr: 0.2274
  >>> New best validation model saved with Avg Corr: 0.2274 <<<
Epoch [1/20], Step 2500, Train Loss: 0.9483, Val Avg Corr: 0.2453
  >>> New best validation model saved with Avg Corr: 0.2453 <<<
Epoch [1/20], Step 3000, Train Loss: 1.0487, Val Avg Corr: 0.2590
  >>> New best validation model saved with Avg Corr: 0.2590 <<<
Epoch [1/20], Step 3500, Train Loss: 0.8655, Val Avg Corr: 0.2852
  >>> New best validation model saved with Avg Corr: 0.2852 <<<
Epoch [1/20], Step 4000, Train Loss: 0.8630, Val Avg Corr: 0.3078
  >>> New best validation model saved with Avg Corr: 0.3078 <<<
Epoch [1/20], Step 4500, Train Loss: 1.1078, Val Avg Corr: 0.3422
  >>> New best validation model saved with Avg Corr: 0.3422 <<<
Epoch [1/20], Step 5000, Train Loss: 0.8830, Val Avg Corr: 0.3613
  >>> New best validation model saved with Avg Corr: 0.3613 <<<
Epoch [1/20], Step 5500, Train Loss: 0.9971, Val Avg Corr: 0.3520
Epoch [1/20], Step 6000, Train Loss: 0.9039, Val Avg Corr: 0.3849
  >>> New best validation model saved with Avg Corr: 0.3849 <<<
Epoch [1/20], Step 6500, Train Loss: 0.8058, Val Avg Corr: 0.3967
  >>> New best validation model saved with Avg Corr: 0.3967 <<<
Epoch [1/20], Step 7000, Train Loss: 0.9612, Val Avg Corr: 0.4057
  >>> New best validation model saved with Avg Corr: 0.4057 <<<
Epoch [1/20], Step 7500, Train Loss: 0.8344, Val Avg Corr: 0.4345
  >>> New best validation model saved with Avg Corr: 0.4345 <<<
Epoch [1/20], Step 8000, Train Loss: 0.8072, Val Avg Corr: 0.4282
Epoch [1/20], Step 8500, Train Loss: 0.8006, Val Avg Corr: 0.4255
Epoch [1/20], Step 9000, Train Loss: 0.8331, Val Avg Corr: 0.4633
  >>> New best validation model saved with Avg Corr: 0.4633 <<<
Epoch [1/20], Step 9500, Train Loss: 0.8211, Val Avg Corr: 0.4440
Epoch [1/20], Step 10000, Train Loss: 0.8505, Val Avg Corr: 0.4311
Epoch [1/20], Step 10500, Train Loss: 0.6906, Val Avg Corr: 0.4590
Epoch [1/20], Step 11000, Train Loss: 0.8518, Val Avg Corr: 0.4592
Epoch [1/20], Step 11500, Train Loss: 0.9448, Val Avg Corr: 0.5071
  >>> New best validation model saved with Avg Corr: 0.5071 <<<
Epoch [1/20], Step 12000, Train Loss: 0.7405, Val Avg Corr: 0.5196
  >>> New best validation model saved with Avg Corr: 0.5196 <<<
Epoch [1/20], Step 12500, Train Loss: 0.8507, Val Avg Corr: 0.5052
Epoch [1/20], Step 13000, Train Loss: 0.7791, Val Avg Corr: 0.5443
  >>> New best validation model saved with Avg Corr: 0.5443 <<<
Epoch [1/20], Step 13500, Train Loss: 0.7835, Val Avg Corr: 0.5683
  >>> New best validation model saved with Avg Corr: 0.5683 <<<
Epoch [1/20], Step 14000, Train Loss: 0.9173, Val Avg Corr: 0.5808
  >>> New best validation model saved with Avg Corr: 0.5808 <<<
Epoch [1/20], Step 14500, Train Loss: 0.7871, Val Avg Corr: 0.6093
  >>> New best validation model saved with Avg Corr: 0.6093 <<<
Epoch [1/20], Step 15000, Train Loss: 0.8347, Val Avg Corr: 0.6388
  >>> New best validation model saved with Avg Corr: 0.6388 <<<
Epoch [1/20], Step 15500, Train Loss: 0.9116, Val Avg Corr: 0.6469
  >>> New best validation model saved with Avg Corr: 0.6469 <<<
Epoch [1/20], Step 16000, Train Loss: 0.6412, Val Avg Corr: 0.6505
  >>> New best validation model saved with Avg Corr: 0.6505 <<<
Epoch [1/20], Step 16500, Train Loss: 0.7986, Val Avg Corr: 0.6396
Epoch [1/20], Step 17000, Train Loss: 0.7702, Val Avg Corr: 0.6589
  >>> New best validation model saved with Avg Corr: 0.6589 <<<
Epoch [1/20], Step 17500, Train Loss: 0.8209, Val Avg Corr: 0.6355
Epoch [1/20], Step 18000, Train Loss: 0.6100, Val Avg Corr: 0.6565
Epoch [1/20], Step 18500, Train Loss: 0.8410, Val Avg Corr: 0.6714
  >>> New best validation model saved with Avg Corr: 0.6714 <<<
Epoch [1/20], Step 19000, Train Loss: 0.6291, Val Avg Corr: 0.6950
  >>> New best validation model saved with Avg Corr: 0.6950 <<<
Epoch [1/20], Step 19500, Train Loss: 0.6414, Val Avg Corr: 0.6941
Epoch [1/20], Step 20000, Train Loss: 0.6049, Val Avg Corr: 0.6992
  >>> New best validation model saved with Avg Corr: 0.6992 <<<
Epoch [1/20], Step 20500, Train Loss: 0.5297, Val Avg Corr: 0.7117
  >>> New best validation model saved with Avg Corr: 0.7117 <<<
Trial change detected: 707 -> 708, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.4865, Val Avg Corr: 0.7090
Epoch [1/20], Step 21500, Train Loss: 0.5190, Val Avg Corr: 0.7032
Epoch [1/20], Step 22000, Train Loss: 0.7045, Val Avg Corr: 0.7211
  >>> New best validation model saved with Avg Corr: 0.7211 <<<
Epoch [1/20], Step 22500, Train Loss: 0.6088, Val Avg Corr: 0.7113
Epoch [1/20], Step 23000, Train Loss: 0.6497, Val Avg Corr: 0.7238
  >>> New best validation model saved with Avg Corr: 0.7238 <<<
Epoch [1/20], Step 23500, Train Loss: 0.4613, Val Avg Corr: 0.7241
  >>> New best validation model saved with Avg Corr: 0.7241 <<<
Epoch [1/20], Step 24000, Train Loss: 0.5528, Val Avg Corr: 0.7394
  >>> New best validation model saved with Avg Corr: 0.7394 <<<
Epoch [1/20], Step 24500, Train Loss: 0.6182, Val Avg Corr: 0.7359
Epoch [1/20], Step 25000, Train Loss: 0.5824, Val Avg Corr: 0.7462
  >>> New best validation model saved with Avg Corr: 0.7462 <<<
Epoch [1/20], Step 25500, Train Loss: 0.6176, Val Avg Corr: 0.7506
  >>> New best validation model saved with Avg Corr: 0.7506 <<<
Epoch [1/20], Step 26000, Train Loss: 0.5307, Val Avg Corr: 0.7500
Epoch [1/20], Step 26500, Train Loss: 0.3698, Val Avg Corr: 0.7539
  >>> New best validation model saved with Avg Corr: 0.7539 <<<
Epoch [1/20], Step 27000, Train Loss: 0.4442, Val Avg Corr: 0.7467
Epoch [1/20], Step 27500, Train Loss: 0.5756, Val Avg Corr: 0.7560
  >>> New best validation model saved with Avg Corr: 0.7560 <<<
Epoch [1/20], Step 28000, Train Loss: 0.4278, Val Avg Corr: 0.7462
Epoch [1/20], Step 28500, Train Loss: 0.5958, Val Avg Corr: 0.7616
  >>> New best validation model saved with Avg Corr: 0.7616 <<<
Epoch [1/20], Step 29000, Train Loss: 0.4407, Val Avg Corr: 0.7625
  >>> New best validation model saved with Avg Corr: 0.7625 <<<
Epoch [1/20], Step 29500, Train Loss: 0.4166, Val Avg Corr: 0.7704
  >>> New best validation model saved with Avg Corr: 0.7704 <<<
Epoch [1/20], Step 30000, Train Loss: 0.3996, Val Avg Corr: 0.7707
  >>> New best validation model saved with Avg Corr: 0.7707 <<<
Epoch [1/20], Step 30500, Train Loss: 0.4546, Val Avg Corr: 0.7761
  >>> New best validation model saved with Avg Corr: 0.7761 <<<
Epoch [1/20], Step 31000, Train Loss: 0.4637, Val Avg Corr: 0.7785
  >>> New best validation model saved with Avg Corr: 0.7785 <<<
Epoch [1/20], Step 31500, Train Loss: 0.6107, Val Avg Corr: 0.7781
Epoch [1/20], Step 32000, Train Loss: 0.3436, Val Avg Corr: 0.7850
  >>> New best validation model saved with Avg Corr: 0.7850 <<<
Epoch [1/20], Step 32500, Train Loss: 0.5564, Val Avg Corr: 0.7773
Epoch [1/20], Step 33000, Train Loss: 0.4646, Val Avg Corr: 0.7802
Epoch [1/20], Step 33500, Train Loss: 0.3635, Val Avg Corr: 0.7773
Epoch [1/20], Step 34000, Train Loss: 0.4067, Val Avg Corr: 0.7811
Epoch [1/20], Step 34500, Train Loss: 0.5529, Val Avg Corr: 0.7790
Epoch [1/20], Step 35000, Train Loss: 0.4883, Val Avg Corr: 0.7811
Epoch [1/20], Step 35500, Train Loss: 0.3915, Val Avg Corr: 0.7838
Epoch [1/20], Step 36000, Train Loss: 0.3584, Val Avg Corr: 0.7843
Epoch [1/20], Step 36500, Train Loss: 0.3516, Val Avg Corr: 0.7921
  >>> New best validation model saved with Avg Corr: 0.7921 <<<
Epoch [1/20], Step 37000, Train Loss: 0.5406, Val Avg Corr: 0.7952
  >>> New best validation model saved with Avg Corr: 0.7952 <<<
Epoch [1/20], Step 37500, Train Loss: 0.3478, Val Avg Corr: 0.7905
Epoch [1/20], Step 38000, Train Loss: 0.6254, Val Avg Corr: 0.7871
Epoch [1/20], Step 38500, Train Loss: 0.4897, Val Avg Corr: 0.7918
Epoch [1/20], Step 39000, Train Loss: 0.5760, Val Avg Corr: 0.7907
Epoch [1/20], Step 39500, Train Loss: 0.4141, Val Avg Corr: 0.7941
Epoch [1/20], Step 40000, Train Loss: 0.4223, Val Avg Corr: 0.7925
Epoch [1/20], Step 40500, Train Loss: 0.4829, Val Avg Corr: 0.7961
  >>> New best validation model saved with Avg Corr: 0.7961 <<<
Epoch [1/20], Step 41000, Train Loss: 0.4226, Val Avg Corr: 0.7962
  >>> New best validation model saved with Avg Corr: 0.7962 <<<
Trial change detected: 1422 -> 1424, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.3908, Val Avg Corr: 0.7899
Epoch [1/20], Step 42000, Train Loss: 0.4749, Val Avg Corr: 0.7997
  >>> New best validation model saved with Avg Corr: 0.7997 <<<
Epoch [1/20], Step 42500, Train Loss: 0.3448, Val Avg Corr: 0.7948
Epoch [1/20], Step 43000, Train Loss: 0.4294, Val Avg Corr: 0.7964
Epoch [1/20], Step 43500, Train Loss: 0.4892, Val Avg Corr: 0.7989
Epoch [1/20], Step 44000, Train Loss: 0.4003, Val Avg Corr: 0.8003
  >>> New best validation model saved with Avg Corr: 0.8003 <<<
Epoch [1/20], Step 44500, Train Loss: 0.4173, Val Avg Corr: 0.7985
Epoch [1/20], Step 45000, Train Loss: 0.3611, Val Avg Corr: 0.8000
Epoch [1/20], Step 45500, Train Loss: 0.4391, Val Avg Corr: 0.7937
Epoch [1/20], Step 46000, Train Loss: 0.4784, Val Avg Corr: 0.8025
  >>> New best validation model saved with Avg Corr: 0.8025 <<<
Epoch [1/20], Step 46500, Train Loss: 0.4941, Val Avg Corr: 0.8047
  >>> New best validation model saved with Avg Corr: 0.8047 <<<
Epoch [1/20], Step 47000, Train Loss: 0.4617, Val Avg Corr: 0.8006
Epoch [1/20], Step 47500, Train Loss: 0.2984, Val Avg Corr: 0.7981
Epoch [1/20], Step 48000, Train Loss: 0.3957, Val Avg Corr: 0.8046
Epoch [1/20], Step 48500, Train Loss: 0.2977, Val Avg Corr: 0.8097
  >>> New best validation model saved with Avg Corr: 0.8097 <<<
Epoch [1/20], Step 49000, Train Loss: 0.4481, Val Avg Corr: 0.8066
Epoch [1/20], Step 49500, Train Loss: 0.4722, Val Avg Corr: 0.8100
  >>> New best validation model saved with Avg Corr: 0.8100 <<<
Epoch [1/20], Step 50000, Train Loss: 0.3851, Val Avg Corr: 0.7996
Epoch [1/20], Step 50500, Train Loss: 0.4675, Val Avg Corr: 0.8114
  >>> New best validation model saved with Avg Corr: 0.8114 <<<
Epoch [1/20], Step 51000, Train Loss: 0.4652, Val Avg Corr: 0.8153
  >>> New best validation model saved with Avg Corr: 0.8153 <<<
Epoch [1/20], Step 51500, Train Loss: 0.3708, Val Avg Corr: 0.8172
  >>> New best validation model saved with Avg Corr: 0.8172 <<<
Epoch [1/20], Step 52000, Train Loss: 0.4014, Val Avg Corr: 0.8097
Epoch [1/20], Step 52500, Train Loss: 0.3632, Val Avg Corr: 0.8080
Epoch [1/20], Step 53000, Train Loss: 0.3942, Val Avg Corr: 0.8104
Epoch [1/20], Step 53500, Train Loss: 0.4887, Val Avg Corr: 0.8050
Epoch [1/20], Step 54000, Train Loss: 0.4115, Val Avg Corr: 0.8170
Epoch [1/20], Step 54500, Train Loss: 0.4451, Val Avg Corr: 0.8113
Epoch [1/20], Step 55000, Train Loss: 0.4747, Val Avg Corr: 0.8157
Epoch [1/20], Step 55500, Train Loss: 0.3825, Val Avg Corr: 0.8147
Epoch [1/20], Step 56000, Train Loss: 0.5061, Val Avg Corr: 0.8068
Epoch [1/20], Step 56500, Train Loss: 0.3946, Val Avg Corr: 0.8161
Epoch [1/20], Step 57000, Train Loss: 0.4859, Val Avg Corr: 0.8150
Epoch [1/20], Step 57500, Train Loss: 0.3651, Val Avg Corr: 0.8193
  >>> New best validation model saved with Avg Corr: 0.8193 <<<
Epoch [1/20], Step 58000, Train Loss: 0.3831, Val Avg Corr: 0.8246
  >>> New best validation model saved with Avg Corr: 0.8246 <<<
Epoch [1/20], Step 58500, Train Loss: 0.3420, Val Avg Corr: 0.8152
Epoch [1/20], Step 59000, Train Loss: 0.3184, Val Avg Corr: 0.8142
Epoch [1/20], Step 59500, Train Loss: 0.3425, Val Avg Corr: 0.8195
Epoch [1/20], Step 60000, Train Loss: 0.3267, Val Avg Corr: 0.8158
Epoch [1/20], Step 60500, Train Loss: 0.3912, Val Avg Corr: 0.8140
Epoch [1/20], Step 61000, Train Loss: 0.3985, Val Avg Corr: 0.8217
Epoch [1/20], Step 61500, Train Loss: 0.3729, Val Avg Corr: 0.8198
Trial change detected: 2134 -> 2136, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.4218, Val Avg Corr: 0.8201
Epoch [1/20], Step 62500, Train Loss: 0.3120, Val Avg Corr: 0.8212
Epoch [1/20], Step 63000, Train Loss: 0.3275, Val Avg Corr: 0.8254
  >>> New best validation model saved with Avg Corr: 0.8254 <<<
Epoch [1/20], Step 63500, Train Loss: 0.3401, Val Avg Corr: 0.8244
Epoch [1/20], Step 64000, Train Loss: 0.4129, Val Avg Corr: 0.8220
Epoch [1/20], Step 64500, Train Loss: 0.4129, Val Avg Corr: 0.8159
Epoch [1/20], Step 65000, Train Loss: 0.3430, Val Avg Corr: 0.8242
Epoch [1/20], Step 65500, Train Loss: 0.3691, Val Avg Corr: 0.8253
Epoch [2/20], Step 500, Train Loss: 0.3790, Val Avg Corr: 0.8250
Epoch [2/20], Step 1000, Train Loss: 0.5631, Val Avg Corr: 0.8229
Epoch [2/20], Step 1500, Train Loss: 0.4771, Val Avg Corr: 0.8272
  >>> New best validation model saved with Avg Corr: 0.8272 <<<
Epoch [2/20], Step 2000, Train Loss: 0.3719, Val Avg Corr: 0.8312
  >>> New best validation model saved with Avg Corr: 0.8312 <<<
Epoch [2/20], Step 2500, Train Loss: 0.2981, Val Avg Corr: 0.8212
Epoch [2/20], Step 3000, Train Loss: 0.4143, Val Avg Corr: 0.8268
Epoch [2/20], Step 3500, Train Loss: 0.3910, Val Avg Corr: 0.8287
Epoch [2/20], Step 4000, Train Loss: 0.3541, Val Avg Corr: 0.8248
Epoch [2/20], Step 4500, Train Loss: 0.4749, Val Avg Corr: 0.8328
  >>> New best validation model saved with Avg Corr: 0.8328 <<<
Epoch [2/20], Step 5000, Train Loss: 0.3600, Val Avg Corr: 0.8288
Epoch [2/20], Step 5500, Train Loss: 0.3064, Val Avg Corr: 0.8243
Epoch [2/20], Step 6000, Train Loss: 0.3656, Val Avg Corr: 0.8290
Epoch [2/20], Step 6500, Train Loss: 0.2745, Val Avg Corr: 0.8266
Epoch [2/20], Step 7000, Train Loss: 0.4091, Val Avg Corr: 0.8287
Epoch [2/20], Step 7500, Train Loss: 0.3501, Val Avg Corr: 0.8257
Epoch [2/20], Step 8000, Train Loss: 0.3387, Val Avg Corr: 0.8240
Epoch [2/20], Step 8500, Train Loss: 0.4176, Val Avg Corr: 0.8145
Epoch [2/20], Step 9000, Train Loss: 0.3231, Val Avg Corr: 0.8235
Epoch [2/20], Step 9500, Train Loss: 0.2772, Val Avg Corr: 0.8251
Epoch [2/20], Step 10000, Train Loss: 0.3372, Val Avg Corr: 0.8105
Epoch [2/20], Step 10500, Train Loss: 0.2296, Val Avg Corr: 0.8219
Epoch [2/20], Step 11000, Train Loss: 0.4091, Val Avg Corr: 0.8223
Epoch [2/20], Step 11500, Train Loss: 0.3737, Val Avg Corr: 0.8263
Epoch [2/20], Step 12000, Train Loss: 0.2920, Val Avg Corr: 0.8244
Epoch [2/20], Step 12500, Train Loss: 0.3715, Val Avg Corr: 0.8184
Epoch [2/20], Step 13000, Train Loss: 0.3421, Val Avg Corr: 0.8205
Epoch [2/20], Step 13500, Train Loss: 0.3692, Val Avg Corr: 0.8198
Epoch [2/20], Step 14000, Train Loss: 0.4041, Val Avg Corr: 0.8219
Epoch [2/20], Step 14500, Train Loss: 0.3229, Val Avg Corr: 0.8255
Epoch [2/20], Step 15000, Train Loss: 0.4261, Val Avg Corr: 0.8241
Epoch [2/20], Step 15500, Train Loss: 0.4524, Val Avg Corr: 0.8295
Epoch [2/20], Step 16000, Train Loss: 0.3389, Val Avg Corr: 0.8255
Epoch [2/20], Step 16500, Train Loss: 0.4137, Val Avg Corr: 0.8257
Epoch [2/20], Step 17000, Train Loss: 0.3307, Val Avg Corr: 0.8209
Epoch [2/20], Step 17500, Train Loss: 0.4485, Val Avg Corr: 0.8229
Epoch [2/20], Step 18000, Train Loss: 0.2930, Val Avg Corr: 0.8226
Epoch [2/20], Step 18500, Train Loss: 0.5294, Val Avg Corr: 0.8245
Epoch [2/20], Step 19000, Train Loss: 0.3160, Val Avg Corr: 0.8263
Epoch [2/20], Step 19500, Train Loss: 0.3512, Val Avg Corr: 0.8252
Epoch [2/20], Step 20000, Train Loss: 0.3780, Val Avg Corr: 0.8230
Epoch [2/20], Step 20500, Train Loss: 0.3050, Val Avg Corr: 0.8272
Trial change detected: 707 -> 708, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.2804, Val Avg Corr: 0.8258
Epoch [2/20], Step 21500, Train Loss: 0.2478, Val Avg Corr: 0.8237
Epoch [2/20], Step 22000, Train Loss: 0.4403, Val Avg Corr: 0.8354
  >>> New best validation model saved with Avg Corr: 0.8354 <<<
Epoch [2/20], Step 22500, Train Loss: 0.4265, Val Avg Corr: 0.8224
Epoch [2/20], Step 23000, Train Loss: 0.4398, Val Avg Corr: 0.8240
Epoch [2/20], Step 23500, Train Loss: 0.2802, Val Avg Corr: 0.8253
Epoch [2/20], Step 24000, Train Loss: 0.3764, Val Avg Corr: 0.8264
Epoch [2/20], Step 24500, Train Loss: 0.4399, Val Avg Corr: 0.8320
Epoch [2/20], Step 25000, Train Loss: 0.3265, Val Avg Corr: 0.8284
Epoch [2/20], Step 25500, Train Loss: 0.3599, Val Avg Corr: 0.8316
Epoch [2/20], Step 26000, Train Loss: 0.3034, Val Avg Corr: 0.8243
Epoch [2/20], Step 26500, Train Loss: 0.2294, Val Avg Corr: 0.8286
Epoch [2/20], Step 27000, Train Loss: 0.3356, Val Avg Corr: 0.8216
Epoch [2/20], Step 27500, Train Loss: 0.3780, Val Avg Corr: 0.8281
Epoch [2/20], Step 28000, Train Loss: 0.2923, Val Avg Corr: 0.8221
Epoch [2/20], Step 28500, Train Loss: 0.3988, Val Avg Corr: 0.8266
Epoch [2/20], Step 29000, Train Loss: 0.3354, Val Avg Corr: 0.8260
Epoch [2/20], Step 29500, Train Loss: 0.3087, Val Avg Corr: 0.8268
Epoch [2/20], Step 30000, Train Loss: 0.3435, Val Avg Corr: 0.8261
Epoch [2/20], Step 30500, Train Loss: 0.3050, Val Avg Corr: 0.8323
Epoch [2/20], Step 31000, Train Loss: 0.3367, Val Avg Corr: 0.8286
Epoch [2/20], Step 31500, Train Loss: 0.4446, Val Avg Corr: 0.8336
Epoch [2/20], Step 32000, Train Loss: 0.2783, Val Avg Corr: 0.8301
Epoch [2/20], Step 32500, Train Loss: 0.4151, Val Avg Corr: 0.8294
Epoch [2/20], Step 33000, Train Loss: 0.3168, Val Avg Corr: 0.8328
Epoch [2/20], Step 33500, Train Loss: 0.2868, Val Avg Corr: 0.8227
Epoch [2/20], Step 34000, Train Loss: 0.2991, Val Avg Corr: 0.8261
Epoch [2/20], Step 34500, Train Loss: 0.4384, Val Avg Corr: 0.8285
Epoch [2/20], Step 35000, Train Loss: 0.3557, Val Avg Corr: 0.8279
Epoch [2/20], Step 35500, Train Loss: 0.3143, Val Avg Corr: 0.8307
Epoch [2/20], Step 36000, Train Loss: 0.2477, Val Avg Corr: 0.8319
Epoch [2/20], Step 36500, Train Loss: 0.2801, Val Avg Corr: 0.8341
Epoch [2/20], Step 37000, Train Loss: 0.3394, Val Avg Corr: 0.8318
Epoch [2/20], Step 37500, Train Loss: 0.2704, Val Avg Corr: 0.8327
Epoch [2/20], Step 38000, Train Loss: 0.4721, Val Avg Corr: 0.8221
Epoch [2/20], Step 38500, Train Loss: 0.3828, Val Avg Corr: 0.8335
Epoch [2/20], Step 39000, Train Loss: 0.4319, Val Avg Corr: 0.8313
Epoch [2/20], Step 39500, Train Loss: 0.3082, Val Avg Corr: 0.8292
Epoch [2/20], Step 40000, Train Loss: 0.3357, Val Avg Corr: 0.8356
  >>> New best validation model saved with Avg Corr: 0.8356 <<<
Epoch [2/20], Step 40500, Train Loss: 0.3928, Val Avg Corr: 0.8317
Epoch [2/20], Step 41000, Train Loss: 0.3325, Val Avg Corr: 0.8346
Trial change detected: 1422 -> 1424, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3264, Val Avg Corr: 0.8358
  >>> New best validation model saved with Avg Corr: 0.8358 <<<
Epoch [2/20], Step 42000, Train Loss: 0.4022, Val Avg Corr: 0.8333
Epoch [2/20], Step 42500, Train Loss: 0.2946, Val Avg Corr: 0.8345
Epoch [2/20], Step 43000, Train Loss: 0.3385, Val Avg Corr: 0.8318
Epoch [2/20], Step 43500, Train Loss: 0.3870, Val Avg Corr: 0.8388
  >>> New best validation model saved with Avg Corr: 0.8388 <<<
Epoch [2/20], Step 44000, Train Loss: 0.3205, Val Avg Corr: 0.8388
  >>> New best validation model saved with Avg Corr: 0.8388 <<<
Epoch [2/20], Step 44500, Train Loss: 0.3753, Val Avg Corr: 0.8296
Epoch [2/20], Step 45000, Train Loss: 0.3206, Val Avg Corr: 0.8316
Epoch [2/20], Step 45500, Train Loss: 0.3668, Val Avg Corr: 0.8273
Epoch [2/20], Step 46000, Train Loss: 0.3670, Val Avg Corr: 0.8309
Epoch [2/20], Step 46500, Train Loss: 0.3966, Val Avg Corr: 0.8318
Epoch [2/20], Step 47000, Train Loss: 0.3576, Val Avg Corr: 0.8357
Epoch [2/20], Step 47500, Train Loss: 0.2484, Val Avg Corr: 0.8306
Epoch [2/20], Step 48000, Train Loss: 0.2950, Val Avg Corr: 0.8329
Epoch [2/20], Step 48500, Train Loss: 0.2650, Val Avg Corr: 0.8382
Epoch [2/20], Step 49000, Train Loss: 0.3645, Val Avg Corr: 0.8311
Epoch [2/20], Step 49500, Train Loss: 0.4070, Val Avg Corr: 0.8322
Epoch [2/20], Step 50000, Train Loss: 0.3163, Val Avg Corr: 0.8272
Epoch [2/20], Step 50500, Train Loss: 0.3919, Val Avg Corr: 0.8370
Epoch [2/20], Step 51000, Train Loss: 0.3972, Val Avg Corr: 0.8364
Epoch [2/20], Step 51500, Train Loss: 0.3529, Val Avg Corr: 0.8300
Epoch [2/20], Step 52000, Train Loss: 0.3470, Val Avg Corr: 0.8349
Epoch [2/20], Step 52500, Train Loss: 0.3247, Val Avg Corr: 0.8328
Epoch [2/20], Step 53000, Train Loss: 0.3693, Val Avg Corr: 0.8331
Epoch [2/20], Step 53500, Train Loss: 0.3855, Val Avg Corr: 0.8271
Epoch [2/20], Step 54000, Train Loss: 0.3459, Val Avg Corr: 0.8341
Epoch [2/20], Step 54500, Train Loss: 0.4188, Val Avg Corr: 0.8322
Epoch [2/20], Step 55000, Train Loss: 0.3611, Val Avg Corr: 0.8302
Epoch [2/20], Step 55500, Train Loss: 0.3331, Val Avg Corr: 0.8324
Epoch [2/20], Step 56000, Train Loss: 0.3893, Val Avg Corr: 0.8362
Epoch [2/20], Step 56500, Train Loss: 0.3145, Val Avg Corr: 0.8362
Epoch [2/20], Step 57000, Train Loss: 0.4222, Val Avg Corr: 0.8426
  >>> New best validation model saved with Avg Corr: 0.8426 <<<
Epoch [2/20], Step 57500, Train Loss: 0.3200, Val Avg Corr: 0.8358
Epoch [2/20], Step 58000, Train Loss: 0.3065, Val Avg Corr: 0.8351
Epoch [2/20], Step 58500, Train Loss: 0.2876, Val Avg Corr: 0.8326
Epoch [2/20], Step 59000, Train Loss: 0.2561, Val Avg Corr: 0.8340
Epoch [2/20], Step 59500, Train Loss: 0.3286, Val Avg Corr: 0.8378
Epoch [2/20], Step 60000, Train Loss: 0.2698, Val Avg Corr: 0.8333
Epoch [2/20], Step 60500, Train Loss: 0.3497, Val Avg Corr: 0.8326
Epoch [2/20], Step 61000, Train Loss: 0.3309, Val Avg Corr: 0.8348
Epoch [2/20], Step 61500, Train Loss: 0.3263, Val Avg Corr: 0.8343
Trial change detected: 2134 -> 2136, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3688, Val Avg Corr: 0.8362
Epoch [2/20], Step 62500, Train Loss: 0.2670, Val Avg Corr: 0.8343
Epoch [2/20], Step 63000, Train Loss: 0.2885, Val Avg Corr: 0.8418
Epoch [2/20], Step 63500, Train Loss: 0.3049, Val Avg Corr: 0.8428
  >>> New best validation model saved with Avg Corr: 0.8428 <<<
Epoch [2/20], Step 64000, Train Loss: 0.3774, Val Avg Corr: 0.8385
Epoch [2/20], Step 64500, Train Loss: 0.3791, Val Avg Corr: 0.8313
Epoch [2/20], Step 65000, Train Loss: 0.2789, Val Avg Corr: 0.8386
Epoch [2/20], Step 65500, Train Loss: 0.3215, Val Avg Corr: 0.8398
Epoch [3/20], Step 500, Train Loss: 0.3115, Val Avg Corr: 0.8344
Epoch [3/20], Step 1000, Train Loss: 0.5096, Val Avg Corr: 0.8391
Epoch [3/20], Step 1500, Train Loss: 0.4054, Val Avg Corr: 0.8399
Epoch [3/20], Step 2000, Train Loss: 0.3132, Val Avg Corr: 0.8382
Epoch [3/20], Step 2500, Train Loss: 0.2647, Val Avg Corr: 0.8354
Epoch [3/20], Step 3000, Train Loss: 0.3529, Val Avg Corr: 0.8412
Epoch [3/20], Step 3500, Train Loss: 0.3579, Val Avg Corr: 0.8423
Epoch [3/20], Step 4000, Train Loss: 0.3141, Val Avg Corr: 0.8415
Epoch [3/20], Step 4500, Train Loss: 0.4169, Val Avg Corr: 0.8360
Epoch [3/20], Step 5000, Train Loss: 0.3438, Val Avg Corr: 0.8360
Epoch [3/20], Step 5500, Train Loss: 0.2682, Val Avg Corr: 0.8368
Epoch [3/20], Step 6000, Train Loss: 0.3320, Val Avg Corr: 0.8378
Epoch [3/20], Step 6500, Train Loss: 0.2534, Val Avg Corr: 0.8373
Epoch [3/20], Step 7000, Train Loss: 0.3510, Val Avg Corr: 0.8393
Epoch [3/20], Step 7500, Train Loss: 0.2984, Val Avg Corr: 0.8339
Epoch [3/20], Step 8000, Train Loss: 0.2840, Val Avg Corr: 0.8380
Epoch [3/20], Step 8500, Train Loss: 0.3940, Val Avg Corr: 0.8328
Epoch [3/20], Step 9000, Train Loss: 0.2964, Val Avg Corr: 0.8335
Epoch [3/20], Step 9500, Train Loss: 0.2331, Val Avg Corr: 0.8378
Epoch [3/20], Step 10000, Train Loss: 0.2978, Val Avg Corr: 0.8314
Epoch [3/20], Step 10500, Train Loss: 0.2109, Val Avg Corr: 0.8366
Epoch [3/20], Step 11000, Train Loss: 0.3514, Val Avg Corr: 0.8400
Epoch [3/20], Step 11500, Train Loss: 0.3185, Val Avg Corr: 0.8359
Epoch [3/20], Step 12000, Train Loss: 0.2842, Val Avg Corr: 0.8339
Epoch [3/20], Step 12500, Train Loss: 0.3404, Val Avg Corr: 0.8386
Epoch [3/20], Step 13000, Train Loss: 0.3107, Val Avg Corr: 0.8374
Epoch [3/20], Step 13500, Train Loss: 0.3065, Val Avg Corr: 0.8373
Epoch [3/20], Step 14000, Train Loss: 0.3750, Val Avg Corr: 0.8330
Epoch [3/20], Step 14500, Train Loss: 0.2875, Val Avg Corr: 0.8341
Epoch [3/20], Step 15000, Train Loss: 0.3792, Val Avg Corr: 0.8377
Epoch [3/20], Step 15500, Train Loss: 0.3925, Val Avg Corr: 0.8374
Epoch [3/20], Step 16000, Train Loss: 0.2954, Val Avg Corr: 0.8369
Epoch [3/20], Step 16500, Train Loss: 0.3938, Val Avg Corr: 0.8389
Epoch [3/20], Step 17000, Train Loss: 0.2905, Val Avg Corr: 0.8375
Epoch [3/20], Step 17500, Train Loss: 0.3915, Val Avg Corr: 0.8365
Epoch [3/20], Step 18000, Train Loss: 0.2594, Val Avg Corr: 0.8361
Epoch [3/20], Step 18500, Train Loss: 0.4911, Val Avg Corr: 0.8370
Epoch [3/20], Step 19000, Train Loss: 0.3043, Val Avg Corr: 0.8396
Epoch [3/20], Step 19500, Train Loss: 0.2954, Val Avg Corr: 0.8398
Epoch [3/20], Step 20000, Train Loss: 0.3344, Val Avg Corr: 0.8383
Epoch [3/20], Step 20500, Train Loss: 0.2682, Val Avg Corr: 0.8385
Trial change detected: 707 -> 708, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.2540, Val Avg Corr: 0.8352
Epoch [3/20], Step 21500, Train Loss: 0.2229, Val Avg Corr: 0.8386
Epoch [3/20], Step 22000, Train Loss: 0.4011, Val Avg Corr: 0.8387
Epoch [3/20], Step 22500, Train Loss: 0.3680, Val Avg Corr: 0.8366
Epoch [3/20], Step 23000, Train Loss: 0.4070, Val Avg Corr: 0.8347
Early stopping triggered after 23000 steps in epoch 3.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8428
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8320, Y=0.7853, Avg=0.8087

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 6) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.1867, Val Avg Corr: 0.0290
  >>> New best validation model saved with Avg Corr: 0.0290 <<<
Epoch [1/20], Step 1000, Train Loss: 1.0176, Val Avg Corr: 0.0180
Epoch [1/20], Step 1500, Train Loss: 1.2429, Val Avg Corr: 0.0991
  >>> New best validation model saved with Avg Corr: 0.0991 <<<
Epoch [1/20], Step 2000, Train Loss: 0.9884, Val Avg Corr: 0.1072
  >>> New best validation model saved with Avg Corr: 0.1072 <<<
Epoch [1/20], Step 2500, Train Loss: 0.8798, Val Avg Corr: 0.1630
  >>> New best validation model saved with Avg Corr: 0.1630 <<<
Epoch [1/20], Step 3000, Train Loss: 0.9993, Val Avg Corr: 0.1609
Epoch [1/20], Step 3500, Train Loss: 0.9860, Val Avg Corr: 0.2079
  >>> New best validation model saved with Avg Corr: 0.2079 <<<
Epoch [1/20], Step 4000, Train Loss: 0.7879, Val Avg Corr: 0.2490
  >>> New best validation model saved with Avg Corr: 0.2490 <<<
Epoch [1/20], Step 4500, Train Loss: 0.8837, Val Avg Corr: 0.2643
  >>> New best validation model saved with Avg Corr: 0.2643 <<<
Epoch [1/20], Step 5000, Train Loss: 1.0908, Val Avg Corr: 0.2624
Epoch [1/20], Step 5500, Train Loss: 1.1313, Val Avg Corr: 0.2990
  >>> New best validation model saved with Avg Corr: 0.2990 <<<
Epoch [1/20], Step 6000, Train Loss: 0.9602, Val Avg Corr: 0.3461
  >>> New best validation model saved with Avg Corr: 0.3461 <<<
Epoch [1/20], Step 6500, Train Loss: 0.8203, Val Avg Corr: 0.3820
  >>> New best validation model saved with Avg Corr: 0.3820 <<<
Epoch [1/20], Step 7000, Train Loss: 0.7911, Val Avg Corr: 0.3861
  >>> New best validation model saved with Avg Corr: 0.3861 <<<
Epoch [1/20], Step 7500, Train Loss: 0.8478, Val Avg Corr: 0.4177
  >>> New best validation model saved with Avg Corr: 0.4177 <<<
Epoch [1/20], Step 8000, Train Loss: 0.8605, Val Avg Corr: 0.4527
  >>> New best validation model saved with Avg Corr: 0.4527 <<<
Epoch [1/20], Step 8500, Train Loss: 0.7667, Val Avg Corr: 0.4486
Epoch [1/20], Step 9000, Train Loss: 0.8590, Val Avg Corr: 0.4697
  >>> New best validation model saved with Avg Corr: 0.4697 <<<
Epoch [1/20], Step 9500, Train Loss: 0.7914, Val Avg Corr: 0.4779
  >>> New best validation model saved with Avg Corr: 0.4779 <<<
Epoch [1/20], Step 10000, Train Loss: 0.6873, Val Avg Corr: 0.4570
Epoch [1/20], Step 10500, Train Loss: 0.7445, Val Avg Corr: 0.4569
Epoch [1/20], Step 11000, Train Loss: 0.7081, Val Avg Corr: 0.4563
Epoch [1/20], Step 11500, Train Loss: 0.8641, Val Avg Corr: 0.5034
  >>> New best validation model saved with Avg Corr: 0.5034 <<<
Epoch [1/20], Step 12000, Train Loss: 0.5821, Val Avg Corr: 0.5375
  >>> New best validation model saved with Avg Corr: 0.5375 <<<
Epoch [1/20], Step 12500, Train Loss: 0.7080, Val Avg Corr: 0.5417
  >>> New best validation model saved with Avg Corr: 0.5417 <<<
Epoch [1/20], Step 13000, Train Loss: 0.7268, Val Avg Corr: 0.5782
  >>> New best validation model saved with Avg Corr: 0.5782 <<<
Epoch [1/20], Step 13500, Train Loss: 0.8212, Val Avg Corr: 0.5865
  >>> New best validation model saved with Avg Corr: 0.5865 <<<
Epoch [1/20], Step 14000, Train Loss: 0.7984, Val Avg Corr: 0.6136
  >>> New best validation model saved with Avg Corr: 0.6136 <<<
Epoch [1/20], Step 14500, Train Loss: 0.7103, Val Avg Corr: 0.6164
  >>> New best validation model saved with Avg Corr: 0.6164 <<<
Epoch [1/20], Step 15000, Train Loss: 0.5557, Val Avg Corr: 0.6108
Epoch [1/20], Step 15500, Train Loss: 0.8170, Val Avg Corr: 0.6321
  >>> New best validation model saved with Avg Corr: 0.6321 <<<
Epoch [1/20], Step 16000, Train Loss: 0.6690, Val Avg Corr: 0.6421
  >>> New best validation model saved with Avg Corr: 0.6421 <<<
Epoch [1/20], Step 16500, Train Loss: 0.5656, Val Avg Corr: 0.6336
Epoch [1/20], Step 17000, Train Loss: 0.6305, Val Avg Corr: 0.6568
  >>> New best validation model saved with Avg Corr: 0.6568 <<<
Epoch [1/20], Step 17500, Train Loss: 0.7039, Val Avg Corr: 0.6488
Epoch [1/20], Step 18000, Train Loss: 0.4692, Val Avg Corr: 0.6451
Epoch [1/20], Step 18500, Train Loss: 0.7823, Val Avg Corr: 0.6613
  >>> New best validation model saved with Avg Corr: 0.6613 <<<
Epoch [1/20], Step 19000, Train Loss: 0.5280, Val Avg Corr: 0.6760
  >>> New best validation model saved with Avg Corr: 0.6760 <<<
Epoch [1/20], Step 19500, Train Loss: 0.5834, Val Avg Corr: 0.6836
  >>> New best validation model saved with Avg Corr: 0.6836 <<<
Epoch [1/20], Step 20000, Train Loss: 0.6076, Val Avg Corr: 0.6798
Epoch [1/20], Step 20500, Train Loss: 0.5167, Val Avg Corr: 0.6786
Trial change detected: 689 -> 690, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.6512, Val Avg Corr: 0.6830
Epoch [1/20], Step 21500, Train Loss: 0.5199, Val Avg Corr: 0.6925
  >>> New best validation model saved with Avg Corr: 0.6925 <<<
Epoch [1/20], Step 22000, Train Loss: 0.5346, Val Avg Corr: 0.6993
  >>> New best validation model saved with Avg Corr: 0.6993 <<<
Epoch [1/20], Step 22500, Train Loss: 0.5395, Val Avg Corr: 0.6973
Epoch [1/20], Step 23000, Train Loss: 0.5931, Val Avg Corr: 0.6911
Epoch [1/20], Step 23500, Train Loss: 0.6295, Val Avg Corr: 0.6780
Epoch [1/20], Step 24000, Train Loss: 0.6325, Val Avg Corr: 0.7026
  >>> New best validation model saved with Avg Corr: 0.7026 <<<
Epoch [1/20], Step 24500, Train Loss: 0.3524, Val Avg Corr: 0.7071
  >>> New best validation model saved with Avg Corr: 0.7071 <<<
Epoch [1/20], Step 25000, Train Loss: 0.5084, Val Avg Corr: 0.7148
  >>> New best validation model saved with Avg Corr: 0.7148 <<<
Epoch [1/20], Step 25500, Train Loss: 0.6093, Val Avg Corr: 0.7175
  >>> New best validation model saved with Avg Corr: 0.7175 <<<
Epoch [1/20], Step 26000, Train Loss: 0.5186, Val Avg Corr: 0.7185
  >>> New best validation model saved with Avg Corr: 0.7185 <<<
Epoch [1/20], Step 26500, Train Loss: 0.5269, Val Avg Corr: 0.7253
  >>> New best validation model saved with Avg Corr: 0.7253 <<<
Epoch [1/20], Step 27000, Train Loss: 0.3909, Val Avg Corr: 0.7257
  >>> New best validation model saved with Avg Corr: 0.7257 <<<
Epoch [1/20], Step 27500, Train Loss: 0.4213, Val Avg Corr: 0.7288
  >>> New best validation model saved with Avg Corr: 0.7288 <<<
Epoch [1/20], Step 28000, Train Loss: 0.4234, Val Avg Corr: 0.7336
  >>> New best validation model saved with Avg Corr: 0.7336 <<<
Epoch [1/20], Step 28500, Train Loss: 0.4407, Val Avg Corr: 0.7364
  >>> New best validation model saved with Avg Corr: 0.7364 <<<
Epoch [1/20], Step 29000, Train Loss: 0.5093, Val Avg Corr: 0.7233
Epoch [1/20], Step 29500, Train Loss: 0.3948, Val Avg Corr: 0.7272
Epoch [1/20], Step 30000, Train Loss: 0.4040, Val Avg Corr: 0.7325
Epoch [1/20], Step 30500, Train Loss: 0.4197, Val Avg Corr: 0.7393
  >>> New best validation model saved with Avg Corr: 0.7393 <<<
Epoch [1/20], Step 31000, Train Loss: 0.4807, Val Avg Corr: 0.7358
Epoch [1/20], Step 31500, Train Loss: 0.4393, Val Avg Corr: 0.7406
  >>> New best validation model saved with Avg Corr: 0.7406 <<<
Epoch [1/20], Step 32000, Train Loss: 0.5497, Val Avg Corr: 0.7365
Epoch [1/20], Step 32500, Train Loss: 0.3780, Val Avg Corr: 0.7386
Epoch [1/20], Step 33000, Train Loss: 0.4292, Val Avg Corr: 0.7310
Epoch [1/20], Step 33500, Train Loss: 0.3572, Val Avg Corr: 0.7435
  >>> New best validation model saved with Avg Corr: 0.7435 <<<
Epoch [1/20], Step 34000, Train Loss: 0.3697, Val Avg Corr: 0.7436
  >>> New best validation model saved with Avg Corr: 0.7436 <<<
Epoch [1/20], Step 34500, Train Loss: 0.5651, Val Avg Corr: 0.7388
Epoch [1/20], Step 35000, Train Loss: 0.4161, Val Avg Corr: 0.7552
  >>> New best validation model saved with Avg Corr: 0.7552 <<<
Epoch [1/20], Step 35500, Train Loss: 0.4623, Val Avg Corr: 0.7481
Epoch [1/20], Step 36000, Train Loss: 0.3158, Val Avg Corr: 0.7564
  >>> New best validation model saved with Avg Corr: 0.7564 <<<
Epoch [1/20], Step 36500, Train Loss: 0.4204, Val Avg Corr: 0.7521
Epoch [1/20], Step 37000, Train Loss: 0.4783, Val Avg Corr: 0.7537
Epoch [1/20], Step 37500, Train Loss: 0.3240, Val Avg Corr: 0.7494
Epoch [1/20], Step 38000, Train Loss: 0.5092, Val Avg Corr: 0.7548
Epoch [1/20], Step 38500, Train Loss: 0.5321, Val Avg Corr: 0.7544
Epoch [1/20], Step 39000, Train Loss: 0.4513, Val Avg Corr: 0.7611
  >>> New best validation model saved with Avg Corr: 0.7611 <<<
Epoch [1/20], Step 39500, Train Loss: 0.4999, Val Avg Corr: 0.7560
Epoch [1/20], Step 40000, Train Loss: 0.3325, Val Avg Corr: 0.7595
Epoch [1/20], Step 40500, Train Loss: 0.4446, Val Avg Corr: 0.7694
  >>> New best validation model saved with Avg Corr: 0.7694 <<<
Epoch [1/20], Step 41000, Train Loss: 0.4966, Val Avg Corr: 0.7614
Trial change detected: 1399 -> 1401, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.3500, Val Avg Corr: 0.7636
Epoch [1/20], Step 42000, Train Loss: 0.3665, Val Avg Corr: 0.7673
Epoch [1/20], Step 42500, Train Loss: 0.4243, Val Avg Corr: 0.7629
Epoch [1/20], Step 43000, Train Loss: 0.4095, Val Avg Corr: 0.7685
Epoch [1/20], Step 43500, Train Loss: 0.4257, Val Avg Corr: 0.7695
  >>> New best validation model saved with Avg Corr: 0.7695 <<<
Epoch [1/20], Step 44000, Train Loss: 0.3787, Val Avg Corr: 0.7673
Epoch [1/20], Step 44500, Train Loss: 0.3911, Val Avg Corr: 0.7691
Epoch [1/20], Step 45000, Train Loss: 0.4751, Val Avg Corr: 0.7652
Epoch [1/20], Step 45500, Train Loss: 0.3588, Val Avg Corr: 0.7649
Epoch [1/20], Step 46000, Train Loss: 0.3713, Val Avg Corr: 0.7655
Epoch [1/20], Step 46500, Train Loss: 0.4672, Val Avg Corr: 0.7690
Epoch [1/20], Step 47000, Train Loss: 0.4315, Val Avg Corr: 0.7721
  >>> New best validation model saved with Avg Corr: 0.7721 <<<
Epoch [1/20], Step 47500, Train Loss: 0.4817, Val Avg Corr: 0.7640
Epoch [1/20], Step 48000, Train Loss: 0.3545, Val Avg Corr: 0.7681
Epoch [1/20], Step 48500, Train Loss: 0.3770, Val Avg Corr: 0.7644
Epoch [1/20], Step 49000, Train Loss: 0.3522, Val Avg Corr: 0.7638
Epoch [1/20], Step 49500, Train Loss: 0.4481, Val Avg Corr: 0.7591
Epoch [1/20], Step 50000, Train Loss: 0.4394, Val Avg Corr: 0.7667
Epoch [1/20], Step 50500, Train Loss: 0.4389, Val Avg Corr: 0.7733
  >>> New best validation model saved with Avg Corr: 0.7733 <<<
Epoch [1/20], Step 51000, Train Loss: 0.3764, Val Avg Corr: 0.7681
Epoch [1/20], Step 51500, Train Loss: 0.4253, Val Avg Corr: 0.7721
Epoch [1/20], Step 52000, Train Loss: 0.3240, Val Avg Corr: 0.7724
Epoch [1/20], Step 52500, Train Loss: 0.3883, Val Avg Corr: 0.7717
Epoch [1/20], Step 53000, Train Loss: 0.4562, Val Avg Corr: 0.7770
  >>> New best validation model saved with Avg Corr: 0.7770 <<<
Epoch [1/20], Step 53500, Train Loss: 0.3574, Val Avg Corr: 0.7713
Epoch [1/20], Step 54000, Train Loss: 0.4659, Val Avg Corr: 0.7716
Epoch [1/20], Step 54500, Train Loss: 0.4145, Val Avg Corr: 0.7742
Epoch [1/20], Step 55000, Train Loss: 0.3558, Val Avg Corr: 0.7750
Epoch [1/20], Step 55500, Train Loss: 0.4752, Val Avg Corr: 0.7747
Epoch [1/20], Step 56000, Train Loss: 0.4495, Val Avg Corr: 0.7729
Epoch [1/20], Step 56500, Train Loss: 0.3635, Val Avg Corr: 0.7780
  >>> New best validation model saved with Avg Corr: 0.7780 <<<
Epoch [1/20], Step 57000, Train Loss: 0.5234, Val Avg Corr: 0.7780
  >>> New best validation model saved with Avg Corr: 0.7780 <<<
Epoch [1/20], Step 57500, Train Loss: 0.4208, Val Avg Corr: 0.7744
Epoch [1/20], Step 58000, Train Loss: 0.4787, Val Avg Corr: 0.7839
  >>> New best validation model saved with Avg Corr: 0.7839 <<<
Epoch [1/20], Step 58500, Train Loss: 0.3670, Val Avg Corr: 0.7724
Epoch [1/20], Step 59000, Train Loss: 0.3652, Val Avg Corr: 0.7786
Epoch [1/20], Step 59500, Train Loss: 0.3890, Val Avg Corr: 0.7755
Epoch [1/20], Step 60000, Train Loss: 0.3731, Val Avg Corr: 0.7788
Epoch [1/20], Step 60500, Train Loss: 0.3268, Val Avg Corr: 0.7737
Epoch [1/20], Step 61000, Train Loss: 0.3247, Val Avg Corr: 0.7862
  >>> New best validation model saved with Avg Corr: 0.7862 <<<
Epoch [1/20], Step 61500, Train Loss: 0.4571, Val Avg Corr: 0.7767
Trial change detected: 2138 -> 2139, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.4041, Val Avg Corr: 0.7745
Epoch [1/20], Step 62500, Train Loss: 0.3663, Val Avg Corr: 0.7803
Epoch [1/20], Step 63000, Train Loss: 0.3064, Val Avg Corr: 0.7822
Epoch [1/20], Step 63500, Train Loss: 0.4123, Val Avg Corr: 0.7817
Epoch [1/20], Step 64000, Train Loss: 0.4011, Val Avg Corr: 0.7820
Epoch [1/20], Step 64500, Train Loss: 0.3995, Val Avg Corr: 0.7758
Epoch [1/20], Step 65000, Train Loss: 0.3478, Val Avg Corr: 0.7788
Epoch [1/20], Step 65500, Train Loss: 0.3739, Val Avg Corr: 0.7897
  >>> New best validation model saved with Avg Corr: 0.7897 <<<
Epoch [2/20], Step 500, Train Loss: 0.3446, Val Avg Corr: 0.7844
Epoch [2/20], Step 1000, Train Loss: 0.4894, Val Avg Corr: 0.7858
Epoch [2/20], Step 1500, Train Loss: 0.5467, Val Avg Corr: 0.7878
Epoch [2/20], Step 2000, Train Loss: 0.3816, Val Avg Corr: 0.7861
Epoch [2/20], Step 2500, Train Loss: 0.2929, Val Avg Corr: 0.7890
Epoch [2/20], Step 3000, Train Loss: 0.3957, Val Avg Corr: 0.7883
Epoch [2/20], Step 3500, Train Loss: 0.4112, Val Avg Corr: 0.7822
Epoch [2/20], Step 4000, Train Loss: 0.2952, Val Avg Corr: 0.7856
Epoch [2/20], Step 4500, Train Loss: 0.3261, Val Avg Corr: 0.7939
  >>> New best validation model saved with Avg Corr: 0.7939 <<<
Epoch [2/20], Step 5000, Train Loss: 0.4630, Val Avg Corr: 0.7916
Epoch [2/20], Step 5500, Train Loss: 0.5024, Val Avg Corr: 0.7958
  >>> New best validation model saved with Avg Corr: 0.7958 <<<
Epoch [2/20], Step 6000, Train Loss: 0.3095, Val Avg Corr: 0.7972
  >>> New best validation model saved with Avg Corr: 0.7972 <<<
Epoch [2/20], Step 6500, Train Loss: 0.3268, Val Avg Corr: 0.7938
Epoch [2/20], Step 7000, Train Loss: 0.3360, Val Avg Corr: 0.7959
Epoch [2/20], Step 7500, Train Loss: 0.3465, Val Avg Corr: 0.7954
Epoch [2/20], Step 8000, Train Loss: 0.4130, Val Avg Corr: 0.7903
Epoch [2/20], Step 8500, Train Loss: 0.4161, Val Avg Corr: 0.7902
Epoch [2/20], Step 9000, Train Loss: 0.3880, Val Avg Corr: 0.7901
Epoch [2/20], Step 9500, Train Loss: 0.3435, Val Avg Corr: 0.7866
Epoch [2/20], Step 10000, Train Loss: 0.2901, Val Avg Corr: 0.7878
Epoch [2/20], Step 10500, Train Loss: 0.3201, Val Avg Corr: 0.7844
Epoch [2/20], Step 11000, Train Loss: 0.3015, Val Avg Corr: 0.7881
Epoch [2/20], Step 11500, Train Loss: 0.3226, Val Avg Corr: 0.7901
Epoch [2/20], Step 12000, Train Loss: 0.2547, Val Avg Corr: 0.7848
Epoch [2/20], Step 12500, Train Loss: 0.3578, Val Avg Corr: 0.7907
Epoch [2/20], Step 13000, Train Loss: 0.3320, Val Avg Corr: 0.7894
Epoch [2/20], Step 13500, Train Loss: 0.3702, Val Avg Corr: 0.7851
Epoch [2/20], Step 14000, Train Loss: 0.4064, Val Avg Corr: 0.7856
Epoch [2/20], Step 14500, Train Loss: 0.3855, Val Avg Corr: 0.7936
Epoch [2/20], Step 15000, Train Loss: 0.2974, Val Avg Corr: 0.7896
Epoch [2/20], Step 15500, Train Loss: 0.4106, Val Avg Corr: 0.7903
Epoch [2/20], Step 16000, Train Loss: 0.3623, Val Avg Corr: 0.7918
Epoch [2/20], Step 16500, Train Loss: 0.3304, Val Avg Corr: 0.7888
Epoch [2/20], Step 17000, Train Loss: 0.3763, Val Avg Corr: 0.7919
Epoch [2/20], Step 17500, Train Loss: 0.3764, Val Avg Corr: 0.7896
Epoch [2/20], Step 18000, Train Loss: 0.2792, Val Avg Corr: 0.7859
Epoch [2/20], Step 18500, Train Loss: 0.5431, Val Avg Corr: 0.7962
Epoch [2/20], Step 19000, Train Loss: 0.2986, Val Avg Corr: 0.7957
Epoch [2/20], Step 19500, Train Loss: 0.3992, Val Avg Corr: 0.7859
Epoch [2/20], Step 20000, Train Loss: 0.3889, Val Avg Corr: 0.7953
Epoch [2/20], Step 20500, Train Loss: 0.2944, Val Avg Corr: 0.7857
Trial change detected: 689 -> 690, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.4595, Val Avg Corr: 0.8000
  >>> New best validation model saved with Avg Corr: 0.8000 <<<
Epoch [2/20], Step 21500, Train Loss: 0.2905, Val Avg Corr: 0.7941
Epoch [2/20], Step 22000, Train Loss: 0.3648, Val Avg Corr: 0.7923
Epoch [2/20], Step 22500, Train Loss: 0.4040, Val Avg Corr: 0.7960
Epoch [2/20], Step 23000, Train Loss: 0.4518, Val Avg Corr: 0.7933
Epoch [2/20], Step 23500, Train Loss: 0.5295, Val Avg Corr: 0.7949
Epoch [2/20], Step 24000, Train Loss: 0.3984, Val Avg Corr: 0.7957
Epoch [2/20], Step 24500, Train Loss: 0.2483, Val Avg Corr: 0.7909
Epoch [2/20], Step 25000, Train Loss: 0.3451, Val Avg Corr: 0.7997
Epoch [2/20], Step 25500, Train Loss: 0.4292, Val Avg Corr: 0.8001
  >>> New best validation model saved with Avg Corr: 0.8001 <<<
Epoch [2/20], Step 26000, Train Loss: 0.3240, Val Avg Corr: 0.8003
  >>> New best validation model saved with Avg Corr: 0.8003 <<<
Epoch [2/20], Step 26500, Train Loss: 0.3842, Val Avg Corr: 0.7980
Epoch [2/20], Step 27000, Train Loss: 0.2719, Val Avg Corr: 0.8031
  >>> New best validation model saved with Avg Corr: 0.8031 <<<
Epoch [2/20], Step 27500, Train Loss: 0.2907, Val Avg Corr: 0.8019
Epoch [2/20], Step 28000, Train Loss: 0.3096, Val Avg Corr: 0.8013
Epoch [2/20], Step 28500, Train Loss: 0.2918, Val Avg Corr: 0.8004
Epoch [2/20], Step 29000, Train Loss: 0.3651, Val Avg Corr: 0.8034
  >>> New best validation model saved with Avg Corr: 0.8034 <<<
Epoch [2/20], Step 29500, Train Loss: 0.3341, Val Avg Corr: 0.8058
  >>> New best validation model saved with Avg Corr: 0.8058 <<<
Epoch [2/20], Step 30000, Train Loss: 0.2913, Val Avg Corr: 0.8032
Epoch [2/20], Step 30500, Train Loss: 0.3181, Val Avg Corr: 0.8033
Epoch [2/20], Step 31000, Train Loss: 0.3453, Val Avg Corr: 0.8019
Epoch [2/20], Step 31500, Train Loss: 0.3677, Val Avg Corr: 0.8017
Epoch [2/20], Step 32000, Train Loss: 0.4088, Val Avg Corr: 0.7981
Epoch [2/20], Step 32500, Train Loss: 0.2968, Val Avg Corr: 0.7936
Epoch [2/20], Step 33000, Train Loss: 0.3683, Val Avg Corr: 0.8010
Epoch [2/20], Step 33500, Train Loss: 0.2696, Val Avg Corr: 0.8053
Epoch [2/20], Step 34000, Train Loss: 0.2891, Val Avg Corr: 0.8095
  >>> New best validation model saved with Avg Corr: 0.8095 <<<
Epoch [2/20], Step 34500, Train Loss: 0.4148, Val Avg Corr: 0.7951
Epoch [2/20], Step 35000, Train Loss: 0.3320, Val Avg Corr: 0.8080
Epoch [2/20], Step 35500, Train Loss: 0.3591, Val Avg Corr: 0.8062
Epoch [2/20], Step 36000, Train Loss: 0.2488, Val Avg Corr: 0.8047
Epoch [2/20], Step 36500, Train Loss: 0.3454, Val Avg Corr: 0.8087
Epoch [2/20], Step 37000, Train Loss: 0.3518, Val Avg Corr: 0.8116
  >>> New best validation model saved with Avg Corr: 0.8116 <<<
Epoch [2/20], Step 37500, Train Loss: 0.2367, Val Avg Corr: 0.8057
Epoch [2/20], Step 38000, Train Loss: 0.4224, Val Avg Corr: 0.8083
Epoch [2/20], Step 38500, Train Loss: 0.4091, Val Avg Corr: 0.8048
Epoch [2/20], Step 39000, Train Loss: 0.3661, Val Avg Corr: 0.8102
Epoch [2/20], Step 39500, Train Loss: 0.3865, Val Avg Corr: 0.8102
Epoch [2/20], Step 40000, Train Loss: 0.2743, Val Avg Corr: 0.8075
Epoch [2/20], Step 40500, Train Loss: 0.3626, Val Avg Corr: 0.8071
Epoch [2/20], Step 41000, Train Loss: 0.4086, Val Avg Corr: 0.8085
Trial change detected: 1399 -> 1401, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.2905, Val Avg Corr: 0.8037
Epoch [2/20], Step 42000, Train Loss: 0.3169, Val Avg Corr: 0.8072
Epoch [2/20], Step 42500, Train Loss: 0.3646, Val Avg Corr: 0.8082
Epoch [2/20], Step 43000, Train Loss: 0.3295, Val Avg Corr: 0.8087
Epoch [2/20], Step 43500, Train Loss: 0.3324, Val Avg Corr: 0.8098
Epoch [2/20], Step 44000, Train Loss: 0.3332, Val Avg Corr: 0.8087
Epoch [2/20], Step 44500, Train Loss: 0.3145, Val Avg Corr: 0.8044
Epoch [2/20], Step 45000, Train Loss: 0.3909, Val Avg Corr: 0.8100
Epoch [2/20], Step 45500, Train Loss: 0.3116, Val Avg Corr: 0.8106
Epoch [2/20], Step 46000, Train Loss: 0.3209, Val Avg Corr: 0.8099
Epoch [2/20], Step 46500, Train Loss: 0.4000, Val Avg Corr: 0.8084
Epoch [2/20], Step 47000, Train Loss: 0.3514, Val Avg Corr: 0.8078
Epoch [2/20], Step 47500, Train Loss: 0.4531, Val Avg Corr: 0.8074
Epoch [2/20], Step 48000, Train Loss: 0.2994, Val Avg Corr: 0.8111
Epoch [2/20], Step 48500, Train Loss: 0.2898, Val Avg Corr: 0.8108
Epoch [2/20], Step 49000, Train Loss: 0.2927, Val Avg Corr: 0.8087
Epoch [2/20], Step 49500, Train Loss: 0.3973, Val Avg Corr: 0.8095
Epoch [2/20], Step 50000, Train Loss: 0.3713, Val Avg Corr: 0.8101
Epoch [2/20], Step 50500, Train Loss: 0.3580, Val Avg Corr: 0.8074
Epoch [2/20], Step 51000, Train Loss: 0.3181, Val Avg Corr: 0.8038
Epoch [2/20], Step 51500, Train Loss: 0.3717, Val Avg Corr: 0.8104
Epoch [2/20], Step 52000, Train Loss: 0.2458, Val Avg Corr: 0.8145
  >>> New best validation model saved with Avg Corr: 0.8145 <<<
Epoch [2/20], Step 52500, Train Loss: 0.3003, Val Avg Corr: 0.8133
Epoch [2/20], Step 53000, Train Loss: 0.3874, Val Avg Corr: 0.8064
Epoch [2/20], Step 53500, Train Loss: 0.2972, Val Avg Corr: 0.8064
Epoch [2/20], Step 54000, Train Loss: 0.3801, Val Avg Corr: 0.8092
Epoch [2/20], Step 54500, Train Loss: 0.3516, Val Avg Corr: 0.8106
Epoch [2/20], Step 55000, Train Loss: 0.2889, Val Avg Corr: 0.8040
Epoch [2/20], Step 55500, Train Loss: 0.4199, Val Avg Corr: 0.8052
Epoch [2/20], Step 56000, Train Loss: 0.3739, Val Avg Corr: 0.8157
  >>> New best validation model saved with Avg Corr: 0.8157 <<<
Epoch [2/20], Step 56500, Train Loss: 0.3025, Val Avg Corr: 0.8130
Epoch [2/20], Step 57000, Train Loss: 0.4099, Val Avg Corr: 0.8062
Epoch [2/20], Step 57500, Train Loss: 0.3657, Val Avg Corr: 0.8069
Epoch [2/20], Step 58000, Train Loss: 0.4089, Val Avg Corr: 0.8148
Epoch [2/20], Step 58500, Train Loss: 0.3023, Val Avg Corr: 0.8062
Epoch [2/20], Step 59000, Train Loss: 0.3520, Val Avg Corr: 0.8034
Epoch [2/20], Step 59500, Train Loss: 0.3479, Val Avg Corr: 0.8132
Epoch [2/20], Step 60000, Train Loss: 0.3105, Val Avg Corr: 0.8119
Epoch [2/20], Step 60500, Train Loss: 0.2812, Val Avg Corr: 0.8156
Epoch [2/20], Step 61000, Train Loss: 0.2525, Val Avg Corr: 0.8152
Epoch [2/20], Step 61500, Train Loss: 0.3981, Val Avg Corr: 0.8109
Trial change detected: 2138 -> 2139, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3323, Val Avg Corr: 0.8099
Epoch [2/20], Step 62500, Train Loss: 0.3049, Val Avg Corr: 0.8077
Epoch [2/20], Step 63000, Train Loss: 0.3030, Val Avg Corr: 0.8167
  >>> New best validation model saved with Avg Corr: 0.8167 <<<
Epoch [2/20], Step 63500, Train Loss: 0.3457, Val Avg Corr: 0.8137
Epoch [2/20], Step 64000, Train Loss: 0.3550, Val Avg Corr: 0.8215
  >>> New best validation model saved with Avg Corr: 0.8215 <<<
Epoch [2/20], Step 64500, Train Loss: 0.3579, Val Avg Corr: 0.8145
Epoch [2/20], Step 65000, Train Loss: 0.2745, Val Avg Corr: 0.8167
Epoch [2/20], Step 65500, Train Loss: 0.3139, Val Avg Corr: 0.8190
Epoch [3/20], Step 500, Train Loss: 0.2790, Val Avg Corr: 0.8156
Epoch [3/20], Step 1000, Train Loss: 0.4554, Val Avg Corr: 0.8214
Epoch [3/20], Step 1500, Train Loss: 0.5037, Val Avg Corr: 0.8128
Epoch [3/20], Step 2000, Train Loss: 0.3273, Val Avg Corr: 0.8193
Epoch [3/20], Step 2500, Train Loss: 0.2479, Val Avg Corr: 0.8195
Epoch [3/20], Step 3000, Train Loss: 0.3471, Val Avg Corr: 0.8182
Epoch [3/20], Step 3500, Train Loss: 0.3712, Val Avg Corr: 0.8157
Epoch [3/20], Step 4000, Train Loss: 0.2683, Val Avg Corr: 0.8180
Epoch [3/20], Step 4500, Train Loss: 0.2817, Val Avg Corr: 0.8161
Epoch [3/20], Step 5000, Train Loss: 0.4379, Val Avg Corr: 0.8207
Epoch [3/20], Step 5500, Train Loss: 0.4514, Val Avg Corr: 0.8206
Epoch [3/20], Step 6000, Train Loss: 0.2701, Val Avg Corr: 0.8198
Epoch [3/20], Step 6500, Train Loss: 0.2982, Val Avg Corr: 0.8178
Epoch [3/20], Step 7000, Train Loss: 0.2994, Val Avg Corr: 0.8176
Epoch [3/20], Step 7500, Train Loss: 0.3203, Val Avg Corr: 0.8202
Epoch [3/20], Step 8000, Train Loss: 0.3715, Val Avg Corr: 0.8203
Epoch [3/20], Step 8500, Train Loss: 0.3353, Val Avg Corr: 0.8166
Epoch [3/20], Step 9000, Train Loss: 0.3390, Val Avg Corr: 0.8127
Epoch [3/20], Step 9500, Train Loss: 0.3271, Val Avg Corr: 0.8182
Epoch [3/20], Step 10000, Train Loss: 0.2712, Val Avg Corr: 0.8210
Epoch [3/20], Step 10500, Train Loss: 0.2970, Val Avg Corr: 0.8133
Epoch [3/20], Step 11000, Train Loss: 0.2594, Val Avg Corr: 0.8147
Epoch [3/20], Step 11500, Train Loss: 0.2828, Val Avg Corr: 0.8097
Epoch [3/20], Step 12000, Train Loss: 0.2514, Val Avg Corr: 0.8158
Epoch [3/20], Step 12500, Train Loss: 0.3494, Val Avg Corr: 0.8200
Epoch [3/20], Step 13000, Train Loss: 0.3110, Val Avg Corr: 0.8157
Epoch [3/20], Step 13500, Train Loss: 0.3249, Val Avg Corr: 0.8153
Epoch [3/20], Step 14000, Train Loss: 0.3722, Val Avg Corr: 0.8136
Epoch [3/20], Step 14500, Train Loss: 0.3742, Val Avg Corr: 0.8165
Epoch [3/20], Step 15000, Train Loss: 0.2600, Val Avg Corr: 0.8177
Epoch [3/20], Step 15500, Train Loss: 0.3805, Val Avg Corr: 0.8231
  >>> New best validation model saved with Avg Corr: 0.8231 <<<
Epoch [3/20], Step 16000, Train Loss: 0.3279, Val Avg Corr: 0.8237
  >>> New best validation model saved with Avg Corr: 0.8237 <<<
Epoch [3/20], Step 16500, Train Loss: 0.2980, Val Avg Corr: 0.8207
Epoch [3/20], Step 17000, Train Loss: 0.3531, Val Avg Corr: 0.8203
Epoch [3/20], Step 17500, Train Loss: 0.3457, Val Avg Corr: 0.8192
Epoch [3/20], Step 18000, Train Loss: 0.2517, Val Avg Corr: 0.8182
Epoch [3/20], Step 18500, Train Loss: 0.4870, Val Avg Corr: 0.8166
Epoch [3/20], Step 19000, Train Loss: 0.2829, Val Avg Corr: 0.8137
Epoch [3/20], Step 19500, Train Loss: 0.3507, Val Avg Corr: 0.8179
Epoch [3/20], Step 20000, Train Loss: 0.3378, Val Avg Corr: 0.8214
Epoch [3/20], Step 20500, Train Loss: 0.2657, Val Avg Corr: 0.8069
Trial change detected: 689 -> 690, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.4210, Val Avg Corr: 0.8157
Epoch [3/20], Step 21500, Train Loss: 0.2524, Val Avg Corr: 0.8249
  >>> New best validation model saved with Avg Corr: 0.8249 <<<
Epoch [3/20], Step 22000, Train Loss: 0.3417, Val Avg Corr: 0.8232
Epoch [3/20], Step 22500, Train Loss: 0.3582, Val Avg Corr: 0.8187
Epoch [3/20], Step 23000, Train Loss: 0.4276, Val Avg Corr: 0.8165
Epoch [3/20], Step 23500, Train Loss: 0.4773, Val Avg Corr: 0.8182
Epoch [3/20], Step 24000, Train Loss: 0.3616, Val Avg Corr: 0.8197
Epoch [3/20], Step 24500, Train Loss: 0.2280, Val Avg Corr: 0.8172
Epoch [3/20], Step 25000, Train Loss: 0.3176, Val Avg Corr: 0.8196
Epoch [3/20], Step 25500, Train Loss: 0.3858, Val Avg Corr: 0.8199
Epoch [3/20], Step 26000, Train Loss: 0.3093, Val Avg Corr: 0.8204
Epoch [3/20], Step 26500, Train Loss: 0.3364, Val Avg Corr: 0.8218
Epoch [3/20], Step 27000, Train Loss: 0.2602, Val Avg Corr: 0.8223
Epoch [3/20], Step 27500, Train Loss: 0.2788, Val Avg Corr: 0.8254
  >>> New best validation model saved with Avg Corr: 0.8254 <<<
Epoch [3/20], Step 28000, Train Loss: 0.2894, Val Avg Corr: 0.8197
Epoch [3/20], Step 28500, Train Loss: 0.2686, Val Avg Corr: 0.8203
Epoch [3/20], Step 29000, Train Loss: 0.3227, Val Avg Corr: 0.8191
Epoch [3/20], Step 29500, Train Loss: 0.3121, Val Avg Corr: 0.8217
Epoch [3/20], Step 30000, Train Loss: 0.2718, Val Avg Corr: 0.8201
Epoch [3/20], Step 30500, Train Loss: 0.2797, Val Avg Corr: 0.8248
Epoch [3/20], Step 31000, Train Loss: 0.3067, Val Avg Corr: 0.8240
Epoch [3/20], Step 31500, Train Loss: 0.3416, Val Avg Corr: 0.8224
Epoch [3/20], Step 32000, Train Loss: 0.3620, Val Avg Corr: 0.8200
Epoch [3/20], Step 32500, Train Loss: 0.2610, Val Avg Corr: 0.8195
Epoch [3/20], Step 33000, Train Loss: 0.3388, Val Avg Corr: 0.8189
Epoch [3/20], Step 33500, Train Loss: 0.2444, Val Avg Corr: 0.8188
Epoch [3/20], Step 34000, Train Loss: 0.2778, Val Avg Corr: 0.8132
Epoch [3/20], Step 34500, Train Loss: 0.4197, Val Avg Corr: 0.8206
Epoch [3/20], Step 35000, Train Loss: 0.3108, Val Avg Corr: 0.8197
Epoch [3/20], Step 35500, Train Loss: 0.3064, Val Avg Corr: 0.8178
Epoch [3/20], Step 36000, Train Loss: 0.2390, Val Avg Corr: 0.8225
Epoch [3/20], Step 36500, Train Loss: 0.3134, Val Avg Corr: 0.8239
Epoch [3/20], Step 37000, Train Loss: 0.3255, Val Avg Corr: 0.8210
Epoch [3/20], Step 37500, Train Loss: 0.2129, Val Avg Corr: 0.8256
  >>> New best validation model saved with Avg Corr: 0.8256 <<<
Epoch [3/20], Step 38000, Train Loss: 0.3658, Val Avg Corr: 0.8245
Epoch [3/20], Step 38500, Train Loss: 0.3843, Val Avg Corr: 0.8228
Epoch [3/20], Step 39000, Train Loss: 0.3513, Val Avg Corr: 0.8233
Epoch [3/20], Step 39500, Train Loss: 0.3695, Val Avg Corr: 0.8159
Epoch [3/20], Step 40000, Train Loss: 0.2621, Val Avg Corr: 0.8189
Epoch [3/20], Step 40500, Train Loss: 0.3370, Val Avg Corr: 0.8251
Epoch [3/20], Step 41000, Train Loss: 0.3722, Val Avg Corr: 0.8276
  >>> New best validation model saved with Avg Corr: 0.8276 <<<
Trial change detected: 1399 -> 1401, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.2644, Val Avg Corr: 0.8243
Epoch [3/20], Step 42000, Train Loss: 0.2860, Val Avg Corr: 0.8244
Epoch [3/20], Step 42500, Train Loss: 0.3169, Val Avg Corr: 0.8209
Epoch [3/20], Step 43000, Train Loss: 0.3061, Val Avg Corr: 0.8220
Epoch [3/20], Step 43500, Train Loss: 0.2959, Val Avg Corr: 0.8234
Epoch [3/20], Step 44000, Train Loss: 0.3079, Val Avg Corr: 0.8248
Epoch [3/20], Step 44500, Train Loss: 0.3095, Val Avg Corr: 0.8201
Epoch [3/20], Step 45000, Train Loss: 0.3616, Val Avg Corr: 0.8155
Epoch [3/20], Step 45500, Train Loss: 0.2915, Val Avg Corr: 0.8210
Epoch [3/20], Step 46000, Train Loss: 0.3019, Val Avg Corr: 0.8296
  >>> New best validation model saved with Avg Corr: 0.8296 <<<
Epoch [3/20], Step 46500, Train Loss: 0.3657, Val Avg Corr: 0.8246
Epoch [3/20], Step 47000, Train Loss: 0.3221, Val Avg Corr: 0.8298
  >>> New best validation model saved with Avg Corr: 0.8298 <<<
Epoch [3/20], Step 47500, Train Loss: 0.4097, Val Avg Corr: 0.8259
Epoch [3/20], Step 48000, Train Loss: 0.2919, Val Avg Corr: 0.8235
Epoch [3/20], Step 48500, Train Loss: 0.2707, Val Avg Corr: 0.8261
Epoch [3/20], Step 49000, Train Loss: 0.2746, Val Avg Corr: 0.8249
Epoch [3/20], Step 49500, Train Loss: 0.3618, Val Avg Corr: 0.8212
Epoch [3/20], Step 50000, Train Loss: 0.3618, Val Avg Corr: 0.8318
  >>> New best validation model saved with Avg Corr: 0.8318 <<<
Epoch [3/20], Step 50500, Train Loss: 0.3382, Val Avg Corr: 0.8191
Epoch [3/20], Step 51000, Train Loss: 0.3026, Val Avg Corr: 0.8220
Epoch [3/20], Step 51500, Train Loss: 0.3435, Val Avg Corr: 0.8223
Epoch [3/20], Step 52000, Train Loss: 0.2350, Val Avg Corr: 0.8252
Epoch [3/20], Step 52500, Train Loss: 0.2845, Val Avg Corr: 0.8325
  >>> New best validation model saved with Avg Corr: 0.8325 <<<
Epoch [3/20], Step 53000, Train Loss: 0.3574, Val Avg Corr: 0.8274
Epoch [3/20], Step 53500, Train Loss: 0.2818, Val Avg Corr: 0.8245
Epoch [3/20], Step 54000, Train Loss: 0.3587, Val Avg Corr: 0.8241
Epoch [3/20], Step 54500, Train Loss: 0.3127, Val Avg Corr: 0.8236
Epoch [3/20], Step 55000, Train Loss: 0.2722, Val Avg Corr: 0.8248
Epoch [3/20], Step 55500, Train Loss: 0.3871, Val Avg Corr: 0.8257
Epoch [3/20], Step 56000, Train Loss: 0.3498, Val Avg Corr: 0.8152
Epoch [3/20], Step 56500, Train Loss: 0.2838, Val Avg Corr: 0.8213
Epoch [3/20], Step 57000, Train Loss: 0.3898, Val Avg Corr: 0.8267
Epoch [3/20], Step 57500, Train Loss: 0.3464, Val Avg Corr: 0.8220
Epoch [3/20], Step 58000, Train Loss: 0.3783, Val Avg Corr: 0.8256
Epoch [3/20], Step 58500, Train Loss: 0.2833, Val Avg Corr: 0.8212
Epoch [3/20], Step 59000, Train Loss: 0.3112, Val Avg Corr: 0.8261
Epoch [3/20], Step 59500, Train Loss: 0.3414, Val Avg Corr: 0.8221
Epoch [3/20], Step 60000, Train Loss: 0.2932, Val Avg Corr: 0.8305
Epoch [3/20], Step 60500, Train Loss: 0.2599, Val Avg Corr: 0.8281
Epoch [3/20], Step 61000, Train Loss: 0.2335, Val Avg Corr: 0.8237
Epoch [3/20], Step 61500, Train Loss: 0.3797, Val Avg Corr: 0.8226
Trial change detected: 2138 -> 2139, resetting states
Epoch [3/20], Step 62000, Train Loss: 0.3107, Val Avg Corr: 0.8251
Epoch [3/20], Step 62500, Train Loss: 0.2935, Val Avg Corr: 0.8236
Epoch [3/20], Step 63000, Train Loss: 0.2820, Val Avg Corr: 0.8276
Epoch [3/20], Step 63500, Train Loss: 0.3413, Val Avg Corr: 0.8236
Epoch [3/20], Step 64000, Train Loss: 0.3071, Val Avg Corr: 0.8240
Epoch [3/20], Step 64500, Train Loss: 0.3300, Val Avg Corr: 0.8191
Epoch [3/20], Step 65000, Train Loss: 0.2696, Val Avg Corr: 0.8263
Epoch [3/20], Step 65500, Train Loss: 0.3122, Val Avg Corr: 0.8308
Epoch [4/20], Step 500, Train Loss: 0.2694, Val Avg Corr: 0.8271
Epoch [4/20], Step 1000, Train Loss: 0.4356, Val Avg Corr: 0.8282
Epoch [4/20], Step 1500, Train Loss: 0.4506, Val Avg Corr: 0.8271
Epoch [4/20], Step 2000, Train Loss: 0.2929, Val Avg Corr: 0.8306
Epoch [4/20], Step 2500, Train Loss: 0.2362, Val Avg Corr: 0.8309
Epoch [4/20], Step 3000, Train Loss: 0.3192, Val Avg Corr: 0.8276
Epoch [4/20], Step 3500, Train Loss: 0.3301, Val Avg Corr: 0.8278
Epoch [4/20], Step 4000, Train Loss: 0.2592, Val Avg Corr: 0.8351
  >>> New best validation model saved with Avg Corr: 0.8351 <<<
Epoch [4/20], Step 4500, Train Loss: 0.2747, Val Avg Corr: 0.8271
Epoch [4/20], Step 5000, Train Loss: 0.3873, Val Avg Corr: 0.8352
  >>> New best validation model saved with Avg Corr: 0.8352 <<<
Epoch [4/20], Step 5500, Train Loss: 0.4330, Val Avg Corr: 0.8306
Epoch [4/20], Step 6000, Train Loss: 0.2608, Val Avg Corr: 0.8317
Epoch [4/20], Step 6500, Train Loss: 0.2722, Val Avg Corr: 0.8305
Epoch [4/20], Step 7000, Train Loss: 0.2853, Val Avg Corr: 0.8351
Epoch [4/20], Step 7500, Train Loss: 0.3038, Val Avg Corr: 0.8266
Epoch [4/20], Step 8000, Train Loss: 0.3320, Val Avg Corr: 0.8302
Epoch [4/20], Step 8500, Train Loss: 0.3405, Val Avg Corr: 0.8251
Epoch [4/20], Step 9000, Train Loss: 0.3322, Val Avg Corr: 0.8283
Epoch [4/20], Step 9500, Train Loss: 0.3027, Val Avg Corr: 0.8256
Epoch [4/20], Step 10000, Train Loss: 0.2537, Val Avg Corr: 0.8267
Epoch [4/20], Step 10500, Train Loss: 0.2674, Val Avg Corr: 0.8197
Epoch [4/20], Step 11000, Train Loss: 0.2402, Val Avg Corr: 0.8288
Epoch [4/20], Step 11500, Train Loss: 0.2675, Val Avg Corr: 0.8269
Epoch [4/20], Step 12000, Train Loss: 0.2490, Val Avg Corr: 0.8288
Epoch [4/20], Step 12500, Train Loss: 0.3528, Val Avg Corr: 0.8233
Epoch [4/20], Step 13000, Train Loss: 0.2988, Val Avg Corr: 0.8222
Epoch [4/20], Step 13500, Train Loss: 0.3069, Val Avg Corr: 0.8268
Epoch [4/20], Step 14000, Train Loss: 0.3593, Val Avg Corr: 0.8224
Epoch [4/20], Step 14500, Train Loss: 0.3455, Val Avg Corr: 0.8306
Epoch [4/20], Step 15000, Train Loss: 0.2417, Val Avg Corr: 0.8261
Epoch [4/20], Step 15500, Train Loss: 0.3552, Val Avg Corr: 0.8275
Epoch [4/20], Step 16000, Train Loss: 0.3185, Val Avg Corr: 0.8249
Epoch [4/20], Step 16500, Train Loss: 0.2827, Val Avg Corr: 0.8259
Epoch [4/20], Step 17000, Train Loss: 0.3269, Val Avg Corr: 0.8289
Epoch [4/20], Step 17500, Train Loss: 0.3361, Val Avg Corr: 0.8298
Epoch [4/20], Step 18000, Train Loss: 0.2326, Val Avg Corr: 0.8253
Epoch [4/20], Step 18500, Train Loss: 0.4494, Val Avg Corr: 0.8250
Epoch [4/20], Step 19000, Train Loss: 0.2868, Val Avg Corr: 0.8272
Epoch [4/20], Step 19500, Train Loss: 0.3389, Val Avg Corr: 0.8286
Epoch [4/20], Step 20000, Train Loss: 0.3234, Val Avg Corr: 0.8271
Epoch [4/20], Step 20500, Train Loss: 0.2495, Val Avg Corr: 0.8228
Trial change detected: 689 -> 690, resetting states
Epoch [4/20], Step 21000, Train Loss: 0.3835, Val Avg Corr: 0.8275
Epoch [4/20], Step 21500, Train Loss: 0.2358, Val Avg Corr: 0.8249
Epoch [4/20], Step 22000, Train Loss: 0.3286, Val Avg Corr: 0.8309
Epoch [4/20], Step 22500, Train Loss: 0.3148, Val Avg Corr: 0.8335
Epoch [4/20], Step 23000, Train Loss: 0.3886, Val Avg Corr: 0.8260
Epoch [4/20], Step 23500, Train Loss: 0.4563, Val Avg Corr: 0.8251
Epoch [4/20], Step 24000, Train Loss: 0.3312, Val Avg Corr: 0.8276
Epoch [4/20], Step 24500, Train Loss: 0.2068, Val Avg Corr: 0.8234
Epoch [4/20], Step 25000, Train Loss: 0.3010, Val Avg Corr: 0.8304
Epoch [4/20], Step 25500, Train Loss: 0.3687, Val Avg Corr: 0.8313
Epoch [4/20], Step 26000, Train Loss: 0.3051, Val Avg Corr: 0.8304
Epoch [4/20], Step 26500, Train Loss: 0.3247, Val Avg Corr: 0.8311
Epoch [4/20], Step 27000, Train Loss: 0.2586, Val Avg Corr: 0.8274
Epoch [4/20], Step 27500, Train Loss: 0.2625, Val Avg Corr: 0.8272
Epoch [4/20], Step 28000, Train Loss: 0.2972, Val Avg Corr: 0.8261
Epoch [4/20], Step 28500, Train Loss: 0.2523, Val Avg Corr: 0.8342
Epoch [4/20], Step 29000, Train Loss: 0.3114, Val Avg Corr: 0.8316
Epoch [4/20], Step 29500, Train Loss: 0.3012, Val Avg Corr: 0.8267
Epoch [4/20], Step 30000, Train Loss: 0.2563, Val Avg Corr: 0.8285
Early stopping triggered after 30000 steps in epoch 4.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8352
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8452, Y=0.8039, Avg=0.8246

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 7) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    0.0    2.0    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    0.0    2.0    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.2123, Val Avg Corr: 0.1035
  >>> New best validation model saved with Avg Corr: 0.1035 <<<
Epoch [1/20], Step 1000, Train Loss: 1.0224, Val Avg Corr: 0.1506
  >>> New best validation model saved with Avg Corr: 0.1506 <<<
Epoch [1/20], Step 1500, Train Loss: 1.2245, Val Avg Corr: 0.1899
  >>> New best validation model saved with Avg Corr: 0.1899 <<<
Epoch [1/20], Step 2000, Train Loss: 0.8951, Val Avg Corr: 0.2119
  >>> New best validation model saved with Avg Corr: 0.2119 <<<
Epoch [1/20], Step 2500, Train Loss: 0.8133, Val Avg Corr: 0.2587
  >>> New best validation model saved with Avg Corr: 0.2587 <<<
Epoch [1/20], Step 3000, Train Loss: 0.9501, Val Avg Corr: 0.2797
  >>> New best validation model saved with Avg Corr: 0.2797 <<<
Epoch [1/20], Step 3500, Train Loss: 0.9670, Val Avg Corr: 0.3021
  >>> New best validation model saved with Avg Corr: 0.3021 <<<
Epoch [1/20], Step 4000, Train Loss: 0.8534, Val Avg Corr: 0.3138
  >>> New best validation model saved with Avg Corr: 0.3138 <<<
Epoch [1/20], Step 4500, Train Loss: 0.9626, Val Avg Corr: 0.3381
  >>> New best validation model saved with Avg Corr: 0.3381 <<<
Epoch [1/20], Step 5000, Train Loss: 0.8912, Val Avg Corr: 0.3575
  >>> New best validation model saved with Avg Corr: 0.3575 <<<
Epoch [1/20], Step 5500, Train Loss: 0.9742, Val Avg Corr: 0.3928
  >>> New best validation model saved with Avg Corr: 0.3928 <<<
Epoch [1/20], Step 6000, Train Loss: 0.6977, Val Avg Corr: 0.3922
Epoch [1/20], Step 6500, Train Loss: 0.8791, Val Avg Corr: 0.4027
  >>> New best validation model saved with Avg Corr: 0.4027 <<<
Epoch [1/20], Step 7000, Train Loss: 0.7436, Val Avg Corr: 0.4455
  >>> New best validation model saved with Avg Corr: 0.4455 <<<
Epoch [1/20], Step 7500, Train Loss: 0.8091, Val Avg Corr: 0.4622
  >>> New best validation model saved with Avg Corr: 0.4622 <<<
Epoch [1/20], Step 8000, Train Loss: 0.6966, Val Avg Corr: 0.4650
  >>> New best validation model saved with Avg Corr: 0.4650 <<<
Epoch [1/20], Step 8500, Train Loss: 0.9431, Val Avg Corr: 0.4923
  >>> New best validation model saved with Avg Corr: 0.4923 <<<
Epoch [1/20], Step 9000, Train Loss: 0.8745, Val Avg Corr: 0.5000
  >>> New best validation model saved with Avg Corr: 0.5000 <<<
Epoch [1/20], Step 9500, Train Loss: 0.6248, Val Avg Corr: 0.4727
Epoch [1/20], Step 10000, Train Loss: 0.7209, Val Avg Corr: 0.4467
Epoch [1/20], Step 10500, Train Loss: 0.7080, Val Avg Corr: 0.4673
Epoch [1/20], Step 11000, Train Loss: 0.6985, Val Avg Corr: 0.4909
Epoch [1/20], Step 11500, Train Loss: 0.8298, Val Avg Corr: 0.5216
  >>> New best validation model saved with Avg Corr: 0.5216 <<<
Epoch [1/20], Step 12000, Train Loss: 0.6073, Val Avg Corr: 0.5397
  >>> New best validation model saved with Avg Corr: 0.5397 <<<
Epoch [1/20], Step 12500, Train Loss: 0.7120, Val Avg Corr: 0.5717
  >>> New best validation model saved with Avg Corr: 0.5717 <<<
Epoch [1/20], Step 13000, Train Loss: 0.7657, Val Avg Corr: 0.5841
  >>> New best validation model saved with Avg Corr: 0.5841 <<<
Epoch [1/20], Step 13500, Train Loss: 0.7039, Val Avg Corr: 0.5925
  >>> New best validation model saved with Avg Corr: 0.5925 <<<
Epoch [1/20], Step 14000, Train Loss: 0.7359, Val Avg Corr: 0.5917
Epoch [1/20], Step 14500, Train Loss: 0.5313, Val Avg Corr: 0.5857
Epoch [1/20], Step 15000, Train Loss: 0.8472, Val Avg Corr: 0.6107
  >>> New best validation model saved with Avg Corr: 0.6107 <<<
Epoch [1/20], Step 15500, Train Loss: 0.7399, Val Avg Corr: 0.6079
Epoch [1/20], Step 16000, Train Loss: 0.5324, Val Avg Corr: 0.6100
Epoch [1/20], Step 16500, Train Loss: 0.6908, Val Avg Corr: 0.6235
  >>> New best validation model saved with Avg Corr: 0.6235 <<<
Epoch [1/20], Step 17000, Train Loss: 0.7178, Val Avg Corr: 0.6248
  >>> New best validation model saved with Avg Corr: 0.6248 <<<
Epoch [1/20], Step 17500, Train Loss: 0.5119, Val Avg Corr: 0.6450
  >>> New best validation model saved with Avg Corr: 0.6450 <<<
Epoch [1/20], Step 18000, Train Loss: 0.5927, Val Avg Corr: 0.6294
Epoch [1/20], Step 18500, Train Loss: 0.6449, Val Avg Corr: 0.6405
Epoch [1/20], Step 19000, Train Loss: 0.6626, Val Avg Corr: 0.6548
  >>> New best validation model saved with Avg Corr: 0.6548 <<<
Epoch [1/20], Step 19500, Train Loss: 0.5674, Val Avg Corr: 0.6560
  >>> New best validation model saved with Avg Corr: 0.6560 <<<
Epoch [1/20], Step 20000, Train Loss: 0.5305, Val Avg Corr: 0.6600
  >>> New best validation model saved with Avg Corr: 0.6600 <<<
Epoch [1/20], Step 20500, Train Loss: 0.4722, Val Avg Corr: 0.6629
  >>> New best validation model saved with Avg Corr: 0.6629 <<<
Trial change detected: 713 -> 715, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.4822, Val Avg Corr: 0.6611
Epoch [1/20], Step 21500, Train Loss: 0.4901, Val Avg Corr: 0.6691
  >>> New best validation model saved with Avg Corr: 0.6691 <<<
Epoch [1/20], Step 22000, Train Loss: 0.5313, Val Avg Corr: 0.6725
  >>> New best validation model saved with Avg Corr: 0.6725 <<<
Epoch [1/20], Step 22500, Train Loss: 0.6906, Val Avg Corr: 0.6741
  >>> New best validation model saved with Avg Corr: 0.6741 <<<
Epoch [1/20], Step 23000, Train Loss: 0.4781, Val Avg Corr: 0.6735
Epoch [1/20], Step 23500, Train Loss: 0.4241, Val Avg Corr: 0.6656
Epoch [1/20], Step 24000, Train Loss: 0.5994, Val Avg Corr: 0.6801
  >>> New best validation model saved with Avg Corr: 0.6801 <<<
Epoch [1/20], Step 24500, Train Loss: 0.5787, Val Avg Corr: 0.6886
  >>> New best validation model saved with Avg Corr: 0.6886 <<<
Epoch [1/20], Step 25000, Train Loss: 0.4815, Val Avg Corr: 0.6991
  >>> New best validation model saved with Avg Corr: 0.6991 <<<
Epoch [1/20], Step 25500, Train Loss: 0.5035, Val Avg Corr: 0.6821
Epoch [1/20], Step 26000, Train Loss: 0.3437, Val Avg Corr: 0.6848
Epoch [1/20], Step 26500, Train Loss: 0.4604, Val Avg Corr: 0.7044
  >>> New best validation model saved with Avg Corr: 0.7044 <<<
Epoch [1/20], Step 27000, Train Loss: 0.4735, Val Avg Corr: 0.6986
Epoch [1/20], Step 27500, Train Loss: 0.4505, Val Avg Corr: 0.6988
Epoch [1/20], Step 28000, Train Loss: 0.5141, Val Avg Corr: 0.7122
  >>> New best validation model saved with Avg Corr: 0.7122 <<<
Epoch [1/20], Step 28500, Train Loss: 0.4551, Val Avg Corr: 0.7019
Epoch [1/20], Step 29000, Train Loss: 0.3728, Val Avg Corr: 0.7072
Epoch [1/20], Step 29500, Train Loss: 0.4359, Val Avg Corr: 0.7172
  >>> New best validation model saved with Avg Corr: 0.7172 <<<
Epoch [1/20], Step 30000, Train Loss: 0.4172, Val Avg Corr: 0.7171
Epoch [1/20], Step 30500, Train Loss: 0.4431, Val Avg Corr: 0.7186
  >>> New best validation model saved with Avg Corr: 0.7186 <<<
Epoch [1/20], Step 31000, Train Loss: 0.4359, Val Avg Corr: 0.7182
Epoch [1/20], Step 31500, Train Loss: 0.4236, Val Avg Corr: 0.7261
  >>> New best validation model saved with Avg Corr: 0.7261 <<<
Epoch [1/20], Step 32000, Train Loss: 0.4693, Val Avg Corr: 0.7178
Epoch [1/20], Step 32500, Train Loss: 0.5092, Val Avg Corr: 0.7196
Epoch [1/20], Step 33000, Train Loss: 0.4058, Val Avg Corr: 0.7271
  >>> New best validation model saved with Avg Corr: 0.7271 <<<
Epoch [1/20], Step 33500, Train Loss: 0.3770, Val Avg Corr: 0.7267
Epoch [1/20], Step 34000, Train Loss: 0.4373, Val Avg Corr: 0.7280
  >>> New best validation model saved with Avg Corr: 0.7280 <<<
Epoch [1/20], Step 34500, Train Loss: 0.4117, Val Avg Corr: 0.7214
Epoch [1/20], Step 35000, Train Loss: 0.4284, Val Avg Corr: 0.7347
  >>> New best validation model saved with Avg Corr: 0.7347 <<<
Epoch [1/20], Step 35500, Train Loss: 0.4201, Val Avg Corr: 0.7333
Epoch [1/20], Step 36000, Train Loss: 0.3642, Val Avg Corr: 0.7346
Epoch [1/20], Step 36500, Train Loss: 0.4151, Val Avg Corr: 0.7184
Epoch [1/20], Step 37000, Train Loss: 0.2909, Val Avg Corr: 0.7306
Epoch [1/20], Step 37500, Train Loss: 0.6104, Val Avg Corr: 0.7388
  >>> New best validation model saved with Avg Corr: 0.7388 <<<
Epoch [1/20], Step 38000, Train Loss: 0.4516, Val Avg Corr: 0.7496
  >>> New best validation model saved with Avg Corr: 0.7496 <<<
Epoch [1/20], Step 38500, Train Loss: 0.4814, Val Avg Corr: 0.7360
Epoch [1/20], Step 39000, Train Loss: 0.4943, Val Avg Corr: 0.7438
Epoch [1/20], Step 39500, Train Loss: 0.4648, Val Avg Corr: 0.7403
Epoch [1/20], Step 40000, Train Loss: 0.4381, Val Avg Corr: 0.7493
Epoch [1/20], Step 40500, Train Loss: 0.4958, Val Avg Corr: 0.7391
Epoch [1/20], Step 41000, Train Loss: 0.3480, Val Avg Corr: 0.7363
Trial change detected: 1426 -> 1429, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.3859, Val Avg Corr: 0.7493
Epoch [1/20], Step 42000, Train Loss: 0.5132, Val Avg Corr: 0.7491
Epoch [1/20], Step 42500, Train Loss: 0.4048, Val Avg Corr: 0.7480
Epoch [1/20], Step 43000, Train Loss: 0.4419, Val Avg Corr: 0.7556
  >>> New best validation model saved with Avg Corr: 0.7556 <<<
Epoch [1/20], Step 43500, Train Loss: 0.5090, Val Avg Corr: 0.7466
Epoch [1/20], Step 44000, Train Loss: 0.3020, Val Avg Corr: 0.7521
Epoch [1/20], Step 44500, Train Loss: 0.3581, Val Avg Corr: 0.7491
Epoch [1/20], Step 45000, Train Loss: 0.4137, Val Avg Corr: 0.7447
Epoch [1/20], Step 45500, Train Loss: 0.3518, Val Avg Corr: 0.7556
Epoch [1/20], Step 46000, Train Loss: 0.3657, Val Avg Corr: 0.7362
Epoch [1/20], Step 46500, Train Loss: 0.6050, Val Avg Corr: 0.7458
Epoch [1/20], Step 47000, Train Loss: 0.4137, Val Avg Corr: 0.7590
  >>> New best validation model saved with Avg Corr: 0.7590 <<<
Epoch [1/20], Step 47500, Train Loss: 0.3067, Val Avg Corr: 0.7631
  >>> New best validation model saved with Avg Corr: 0.7631 <<<
Epoch [1/20], Step 48000, Train Loss: 0.3850, Val Avg Corr: 0.7621
Epoch [1/20], Step 48500, Train Loss: 0.3328, Val Avg Corr: 0.7497
Epoch [1/20], Step 49000, Train Loss: 0.4722, Val Avg Corr: 0.7581
Epoch [1/20], Step 49500, Train Loss: 0.4534, Val Avg Corr: 0.7624
Epoch [1/20], Step 50000, Train Loss: 0.3629, Val Avg Corr: 0.7507
Epoch [1/20], Step 50500, Train Loss: 0.4368, Val Avg Corr: 0.7692
  >>> New best validation model saved with Avg Corr: 0.7692 <<<
Epoch [1/20], Step 51000, Train Loss: 0.3721, Val Avg Corr: 0.7697
  >>> New best validation model saved with Avg Corr: 0.7697 <<<
Epoch [1/20], Step 51500, Train Loss: 0.3660, Val Avg Corr: 0.7576
Epoch [1/20], Step 52000, Train Loss: 0.4527, Val Avg Corr: 0.7666
Epoch [1/20], Step 52500, Train Loss: 0.3761, Val Avg Corr: 0.7553
Epoch [1/20], Step 53000, Train Loss: 0.4508, Val Avg Corr: 0.7667
Epoch [1/20], Step 53500, Train Loss: 0.4751, Val Avg Corr: 0.7652
Epoch [1/20], Step 54000, Train Loss: 0.4024, Val Avg Corr: 0.7648
Epoch [1/20], Step 54500, Train Loss: 0.3892, Val Avg Corr: 0.7649
Epoch [1/20], Step 55000, Train Loss: 0.5085, Val Avg Corr: 0.7632
Epoch [1/20], Step 55500, Train Loss: 0.3736, Val Avg Corr: 0.7772
  >>> New best validation model saved with Avg Corr: 0.7772 <<<
Epoch [1/20], Step 56000, Train Loss: 0.4337, Val Avg Corr: 0.7835
  >>> New best validation model saved with Avg Corr: 0.7835 <<<
Epoch [1/20], Step 56500, Train Loss: 0.4235, Val Avg Corr: 0.7770
Epoch [1/20], Step 57000, Train Loss: 0.4198, Val Avg Corr: 0.7638
Epoch [1/20], Step 57500, Train Loss: 0.3380, Val Avg Corr: 0.7731
Epoch [1/20], Step 58000, Train Loss: 0.3530, Val Avg Corr: 0.7810
Epoch [1/20], Step 58500, Train Loss: 0.4173, Val Avg Corr: 0.7722
Epoch [1/20], Step 59000, Train Loss: 0.3603, Val Avg Corr: 0.7773
Epoch [1/20], Step 59500, Train Loss: 0.3863, Val Avg Corr: 0.7667
Epoch [1/20], Step 60000, Train Loss: 0.4387, Val Avg Corr: 0.7738
Epoch [1/20], Step 60500, Train Loss: 0.3287, Val Avg Corr: 0.7624
Epoch [1/20], Step 61000, Train Loss: 0.2588, Val Avg Corr: 0.7763
Epoch [1/20], Step 61500, Train Loss: 0.4550, Val Avg Corr: 0.7752
Trial change detected: 2147 -> 2148, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3968, Val Avg Corr: 0.7807
Epoch [1/20], Step 62500, Train Loss: 0.3452, Val Avg Corr: 0.7922
  >>> New best validation model saved with Avg Corr: 0.7922 <<<
Epoch [1/20], Step 63000, Train Loss: 0.3168, Val Avg Corr: 0.7837
Epoch [1/20], Step 63500, Train Loss: 0.3810, Val Avg Corr: 0.7843
Epoch [1/20], Step 64000, Train Loss: 0.3871, Val Avg Corr: 0.7827
Epoch [1/20], Step 64500, Train Loss: 0.3868, Val Avg Corr: 0.7798
Epoch [1/20], Step 65000, Train Loss: 0.3527, Val Avg Corr: 0.7742
Epoch [1/20], Step 65500, Train Loss: 0.3783, Val Avg Corr: 0.7779
Epoch [2/20], Step 500, Train Loss: 0.4171, Val Avg Corr: 0.7842
Epoch [2/20], Step 1000, Train Loss: 0.4338, Val Avg Corr: 0.7852
Epoch [2/20], Step 1500, Train Loss: 0.4740, Val Avg Corr: 0.7779
Epoch [2/20], Step 2000, Train Loss: 0.3368, Val Avg Corr: 0.7791
Epoch [2/20], Step 2500, Train Loss: 0.2505, Val Avg Corr: 0.7738
Epoch [2/20], Step 3000, Train Loss: 0.4772, Val Avg Corr: 0.7809
Epoch [2/20], Step 3500, Train Loss: 0.3775, Val Avg Corr: 0.7777
Epoch [2/20], Step 4000, Train Loss: 0.3326, Val Avg Corr: 0.7810
Epoch [2/20], Step 4500, Train Loss: 0.4523, Val Avg Corr: 0.7849
Epoch [2/20], Step 5000, Train Loss: 0.3168, Val Avg Corr: 0.7808
Epoch [2/20], Step 5500, Train Loss: 0.4047, Val Avg Corr: 0.7814
Epoch [2/20], Step 6000, Train Loss: 0.2528, Val Avg Corr: 0.7826
Epoch [2/20], Step 6500, Train Loss: 0.4096, Val Avg Corr: 0.7821
Epoch [2/20], Step 7000, Train Loss: 0.3794, Val Avg Corr: 0.7766
Epoch [2/20], Step 7500, Train Loss: 0.3891, Val Avg Corr: 0.7698
Epoch [2/20], Step 8000, Train Loss: 0.3087, Val Avg Corr: 0.7732
Epoch [2/20], Step 8500, Train Loss: 0.5045, Val Avg Corr: 0.7795
Epoch [2/20], Step 9000, Train Loss: 0.3893, Val Avg Corr: 0.7812
Epoch [2/20], Step 9500, Train Loss: 0.3057, Val Avg Corr: 0.7855
Epoch [2/20], Step 10000, Train Loss: 0.3745, Val Avg Corr: 0.7748
Epoch [2/20], Step 10500, Train Loss: 0.2677, Val Avg Corr: 0.7763
Epoch [2/20], Step 11000, Train Loss: 0.3532, Val Avg Corr: 0.7754
Epoch [2/20], Step 11500, Train Loss: 0.3478, Val Avg Corr: 0.7871
Epoch [2/20], Step 12000, Train Loss: 0.3058, Val Avg Corr: 0.7836
Epoch [2/20], Step 12500, Train Loss: 0.3511, Val Avg Corr: 0.7833
Epoch [2/20], Step 13000, Train Loss: 0.3527, Val Avg Corr: 0.7811
Epoch [2/20], Step 13500, Train Loss: 0.3355, Val Avg Corr: 0.7812
Epoch [2/20], Step 14000, Train Loss: 0.3897, Val Avg Corr: 0.7890
Epoch [2/20], Step 14500, Train Loss: 0.2942, Val Avg Corr: 0.7900
Epoch [2/20], Step 15000, Train Loss: 0.4412, Val Avg Corr: 0.7887
Epoch [2/20], Step 15500, Train Loss: 0.4373, Val Avg Corr: 0.7901
Epoch [2/20], Step 16000, Train Loss: 0.3883, Val Avg Corr: 0.7917
Epoch [2/20], Step 16500, Train Loss: 0.4616, Val Avg Corr: 0.7980
  >>> New best validation model saved with Avg Corr: 0.7980 <<<
Epoch [2/20], Step 17000, Train Loss: 0.3476, Val Avg Corr: 0.7936
Epoch [2/20], Step 17500, Train Loss: 0.2902, Val Avg Corr: 0.7931
Epoch [2/20], Step 18000, Train Loss: 0.3886, Val Avg Corr: 0.7866
Epoch [2/20], Step 18500, Train Loss: 0.4044, Val Avg Corr: 0.8001
  >>> New best validation model saved with Avg Corr: 0.8001 <<<
Epoch [2/20], Step 19000, Train Loss: 0.4174, Val Avg Corr: 0.7933
Epoch [2/20], Step 19500, Train Loss: 0.3526, Val Avg Corr: 0.7903
Epoch [2/20], Step 20000, Train Loss: 0.3704, Val Avg Corr: 0.7820
Epoch [2/20], Step 20500, Train Loss: 0.3199, Val Avg Corr: 0.7926
Trial change detected: 713 -> 715, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.2634, Val Avg Corr: 0.7975
Epoch [2/20], Step 21500, Train Loss: 0.3661, Val Avg Corr: 0.7880
Epoch [2/20], Step 22000, Train Loss: 0.4172, Val Avg Corr: 0.7858
Epoch [2/20], Step 22500, Train Loss: 0.4932, Val Avg Corr: 0.7943
Epoch [2/20], Step 23000, Train Loss: 0.3844, Val Avg Corr: 0.7985
Epoch [2/20], Step 23500, Train Loss: 0.2699, Val Avg Corr: 0.7981
Epoch [2/20], Step 24000, Train Loss: 0.4128, Val Avg Corr: 0.7995
Epoch [2/20], Step 24500, Train Loss: 0.4300, Val Avg Corr: 0.8018
  >>> New best validation model saved with Avg Corr: 0.8018 <<<
Epoch [2/20], Step 25000, Train Loss: 0.3137, Val Avg Corr: 0.7970
Epoch [2/20], Step 25500, Train Loss: 0.3641, Val Avg Corr: 0.7789
Epoch [2/20], Step 26000, Train Loss: 0.2345, Val Avg Corr: 0.7954
Epoch [2/20], Step 26500, Train Loss: 0.3621, Val Avg Corr: 0.7909
Epoch [2/20], Step 27000, Train Loss: 0.3523, Val Avg Corr: 0.7896
Epoch [2/20], Step 27500, Train Loss: 0.3344, Val Avg Corr: 0.7923
Epoch [2/20], Step 28000, Train Loss: 0.3633, Val Avg Corr: 0.7904
Epoch [2/20], Step 28500, Train Loss: 0.3746, Val Avg Corr: 0.7887
Epoch [2/20], Step 29000, Train Loss: 0.2627, Val Avg Corr: 0.7854
Epoch [2/20], Step 29500, Train Loss: 0.3411, Val Avg Corr: 0.8018
Epoch [2/20], Step 30000, Train Loss: 0.2651, Val Avg Corr: 0.7962
Epoch [2/20], Step 30500, Train Loss: 0.3463, Val Avg Corr: 0.7998
Epoch [2/20], Step 31000, Train Loss: 0.3671, Val Avg Corr: 0.8011
Epoch [2/20], Step 31500, Train Loss: 0.3382, Val Avg Corr: 0.7990
Epoch [2/20], Step 32000, Train Loss: 0.3629, Val Avg Corr: 0.7924
Epoch [2/20], Step 32500, Train Loss: 0.3460, Val Avg Corr: 0.7862
Epoch [2/20], Step 33000, Train Loss: 0.3139, Val Avg Corr: 0.8013
Epoch [2/20], Step 33500, Train Loss: 0.2652, Val Avg Corr: 0.7960
Epoch [2/20], Step 34000, Train Loss: 0.3051, Val Avg Corr: 0.7954
Epoch [2/20], Step 34500, Train Loss: 0.3235, Val Avg Corr: 0.7884
Epoch [2/20], Step 35000, Train Loss: 0.3740, Val Avg Corr: 0.7967
Epoch [2/20], Step 35500, Train Loss: 0.3305, Val Avg Corr: 0.7993
Epoch [2/20], Step 36000, Train Loss: 0.2852, Val Avg Corr: 0.8020
  >>> New best validation model saved with Avg Corr: 0.8020 <<<
Epoch [2/20], Step 36500, Train Loss: 0.3109, Val Avg Corr: 0.7890
Epoch [2/20], Step 37000, Train Loss: 0.2253, Val Avg Corr: 0.8001
Epoch [2/20], Step 37500, Train Loss: 0.4735, Val Avg Corr: 0.7988
Epoch [2/20], Step 38000, Train Loss: 0.3698, Val Avg Corr: 0.8018
Epoch [2/20], Step 38500, Train Loss: 0.3572, Val Avg Corr: 0.7981
Epoch [2/20], Step 39000, Train Loss: 0.4024, Val Avg Corr: 0.8013
Epoch [2/20], Step 39500, Train Loss: 0.3945, Val Avg Corr: 0.7953
Epoch [2/20], Step 40000, Train Loss: 0.3696, Val Avg Corr: 0.7940
Epoch [2/20], Step 40500, Train Loss: 0.3713, Val Avg Corr: 0.7948
Epoch [2/20], Step 41000, Train Loss: 0.2675, Val Avg Corr: 0.8004
Trial change detected: 1426 -> 1429, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3303, Val Avg Corr: 0.7971
Epoch [2/20], Step 42000, Train Loss: 0.4145, Val Avg Corr: 0.7979
Epoch [2/20], Step 42500, Train Loss: 0.3485, Val Avg Corr: 0.7882
Epoch [2/20], Step 43000, Train Loss: 0.3731, Val Avg Corr: 0.8022
  >>> New best validation model saved with Avg Corr: 0.8022 <<<
Epoch [2/20], Step 43500, Train Loss: 0.3779, Val Avg Corr: 0.7920
Epoch [2/20], Step 44000, Train Loss: 0.2987, Val Avg Corr: 0.7994
Epoch [2/20], Step 44500, Train Loss: 0.3148, Val Avg Corr: 0.7933
Epoch [2/20], Step 45000, Train Loss: 0.3523, Val Avg Corr: 0.7964
Epoch [2/20], Step 45500, Train Loss: 0.2987, Val Avg Corr: 0.7983
Epoch [2/20], Step 46000, Train Loss: 0.3150, Val Avg Corr: 0.7880
Epoch [2/20], Step 46500, Train Loss: 0.4781, Val Avg Corr: 0.7953
Epoch [2/20], Step 47000, Train Loss: 0.3256, Val Avg Corr: 0.8022
Epoch [2/20], Step 47500, Train Loss: 0.2307, Val Avg Corr: 0.8046
  >>> New best validation model saved with Avg Corr: 0.8046 <<<
Epoch [2/20], Step 48000, Train Loss: 0.3309, Val Avg Corr: 0.8063
  >>> New best validation model saved with Avg Corr: 0.8063 <<<
Epoch [2/20], Step 48500, Train Loss: 0.2897, Val Avg Corr: 0.7989
Epoch [2/20], Step 49000, Train Loss: 0.3887, Val Avg Corr: 0.8020
Epoch [2/20], Step 49500, Train Loss: 0.3742, Val Avg Corr: 0.8071
  >>> New best validation model saved with Avg Corr: 0.8071 <<<
Epoch [2/20], Step 50000, Train Loss: 0.3059, Val Avg Corr: 0.7923
Epoch [2/20], Step 50500, Train Loss: 0.3953, Val Avg Corr: 0.8059
Epoch [2/20], Step 51000, Train Loss: 0.3129, Val Avg Corr: 0.8060
Epoch [2/20], Step 51500, Train Loss: 0.3188, Val Avg Corr: 0.8033
Epoch [2/20], Step 52000, Train Loss: 0.3988, Val Avg Corr: 0.7995
Epoch [2/20], Step 52500, Train Loss: 0.3224, Val Avg Corr: 0.8003
Epoch [2/20], Step 53000, Train Loss: 0.3674, Val Avg Corr: 0.8040
Epoch [2/20], Step 53500, Train Loss: 0.3769, Val Avg Corr: 0.8070
Epoch [2/20], Step 54000, Train Loss: 0.3719, Val Avg Corr: 0.8000
Epoch [2/20], Step 54500, Train Loss: 0.3262, Val Avg Corr: 0.8063
Epoch [2/20], Step 55000, Train Loss: 0.4244, Val Avg Corr: 0.7994
Epoch [2/20], Step 55500, Train Loss: 0.3171, Val Avg Corr: 0.8102
  >>> New best validation model saved with Avg Corr: 0.8102 <<<
Epoch [2/20], Step 56000, Train Loss: 0.3624, Val Avg Corr: 0.8096
Epoch [2/20], Step 56500, Train Loss: 0.3680, Val Avg Corr: 0.8109
  >>> New best validation model saved with Avg Corr: 0.8109 <<<
Epoch [2/20], Step 57000, Train Loss: 0.3667, Val Avg Corr: 0.8006
Epoch [2/20], Step 57500, Train Loss: 0.2746, Val Avg Corr: 0.8087
Epoch [2/20], Step 58000, Train Loss: 0.3130, Val Avg Corr: 0.8073
Epoch [2/20], Step 58500, Train Loss: 0.3441, Val Avg Corr: 0.8114
  >>> New best validation model saved with Avg Corr: 0.8114 <<<
Epoch [2/20], Step 59000, Train Loss: 0.3466, Val Avg Corr: 0.8149
  >>> New best validation model saved with Avg Corr: 0.8149 <<<
Epoch [2/20], Step 59500, Train Loss: 0.3135, Val Avg Corr: 0.7982
Epoch [2/20], Step 60000, Train Loss: 0.3665, Val Avg Corr: 0.8007
Epoch [2/20], Step 60500, Train Loss: 0.2843, Val Avg Corr: 0.7920
Epoch [2/20], Step 61000, Train Loss: 0.2223, Val Avg Corr: 0.8030
Epoch [2/20], Step 61500, Train Loss: 0.3761, Val Avg Corr: 0.8038
Trial change detected: 2147 -> 2148, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3120, Val Avg Corr: 0.8076
Epoch [2/20], Step 62500, Train Loss: 0.3354, Val Avg Corr: 0.8127
Epoch [2/20], Step 63000, Train Loss: 0.2807, Val Avg Corr: 0.8156
  >>> New best validation model saved with Avg Corr: 0.8156 <<<
Epoch [2/20], Step 63500, Train Loss: 0.3343, Val Avg Corr: 0.8079
Epoch [2/20], Step 64000, Train Loss: 0.3637, Val Avg Corr: 0.8107
Epoch [2/20], Step 64500, Train Loss: 0.3590, Val Avg Corr: 0.8035
Epoch [2/20], Step 65000, Train Loss: 0.3104, Val Avg Corr: 0.8000
Epoch [2/20], Step 65500, Train Loss: 0.3110, Val Avg Corr: 0.7988
Epoch [3/20], Step 500, Train Loss: 0.3668, Val Avg Corr: 0.8080
Epoch [3/20], Step 1000, Train Loss: 0.3851, Val Avg Corr: 0.8084
Epoch [3/20], Step 1500, Train Loss: 0.4156, Val Avg Corr: 0.8132
Epoch [3/20], Step 2000, Train Loss: 0.3023, Val Avg Corr: 0.8101
Epoch [3/20], Step 2500, Train Loss: 0.2402, Val Avg Corr: 0.8098
Epoch [3/20], Step 3000, Train Loss: 0.4206, Val Avg Corr: 0.8100
Epoch [3/20], Step 3500, Train Loss: 0.3595, Val Avg Corr: 0.8067
Epoch [3/20], Step 4000, Train Loss: 0.2994, Val Avg Corr: 0.8095
Epoch [3/20], Step 4500, Train Loss: 0.3949, Val Avg Corr: 0.8036
Epoch [3/20], Step 5000, Train Loss: 0.2790, Val Avg Corr: 0.8072
Epoch [3/20], Step 5500, Train Loss: 0.3629, Val Avg Corr: 0.8094
Epoch [3/20], Step 6000, Train Loss: 0.2259, Val Avg Corr: 0.8064
Epoch [3/20], Step 6500, Train Loss: 0.3665, Val Avg Corr: 0.8088
Epoch [3/20], Step 7000, Train Loss: 0.3393, Val Avg Corr: 0.8033
Epoch [3/20], Step 7500, Train Loss: 0.3416, Val Avg Corr: 0.7935
Epoch [3/20], Step 8000, Train Loss: 0.2662, Val Avg Corr: 0.7953
Epoch [3/20], Step 8500, Train Loss: 0.4689, Val Avg Corr: 0.8077
Epoch [3/20], Step 9000, Train Loss: 0.3225, Val Avg Corr: 0.8056
Epoch [3/20], Step 9500, Train Loss: 0.2802, Val Avg Corr: 0.8155
Epoch [3/20], Step 10000, Train Loss: 0.3342, Val Avg Corr: 0.8082
Epoch [3/20], Step 10500, Train Loss: 0.2421, Val Avg Corr: 0.8063
Epoch [3/20], Step 11000, Train Loss: 0.3052, Val Avg Corr: 0.8052
Epoch [3/20], Step 11500, Train Loss: 0.3018, Val Avg Corr: 0.8069
Epoch [3/20], Step 12000, Train Loss: 0.2960, Val Avg Corr: 0.8048
Epoch [3/20], Step 12500, Train Loss: 0.3209, Val Avg Corr: 0.8038
Epoch [3/20], Step 13000, Train Loss: 0.2958, Val Avg Corr: 0.7992
Epoch [3/20], Step 13500, Train Loss: 0.3229, Val Avg Corr: 0.8081
Epoch [3/20], Step 14000, Train Loss: 0.3387, Val Avg Corr: 0.8145
Epoch [3/20], Step 14500, Train Loss: 0.2613, Val Avg Corr: 0.8117
Epoch [3/20], Step 15000, Train Loss: 0.4029, Val Avg Corr: 0.8048
Epoch [3/20], Step 15500, Train Loss: 0.3763, Val Avg Corr: 0.8158
  >>> New best validation model saved with Avg Corr: 0.8158 <<<
Epoch [3/20], Step 16000, Train Loss: 0.3595, Val Avg Corr: 0.8118
Epoch [3/20], Step 16500, Train Loss: 0.4354, Val Avg Corr: 0.8137
Epoch [3/20], Step 17000, Train Loss: 0.3102, Val Avg Corr: 0.8147
Epoch [3/20], Step 17500, Train Loss: 0.2624, Val Avg Corr: 0.8170
  >>> New best validation model saved with Avg Corr: 0.8170 <<<
Epoch [3/20], Step 18000, Train Loss: 0.3618, Val Avg Corr: 0.8089
Epoch [3/20], Step 18500, Train Loss: 0.3518, Val Avg Corr: 0.8215
  >>> New best validation model saved with Avg Corr: 0.8215 <<<
Epoch [3/20], Step 19000, Train Loss: 0.3841, Val Avg Corr: 0.8170
Epoch [3/20], Step 19500, Train Loss: 0.3307, Val Avg Corr: 0.8096
Epoch [3/20], Step 20000, Train Loss: 0.3253, Val Avg Corr: 0.8090
Epoch [3/20], Step 20500, Train Loss: 0.2717, Val Avg Corr: 0.8182
Trial change detected: 713 -> 715, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.2310, Val Avg Corr: 0.8185
Epoch [3/20], Step 21500, Train Loss: 0.3257, Val Avg Corr: 0.8233
  >>> New best validation model saved with Avg Corr: 0.8233 <<<
Epoch [3/20], Step 22000, Train Loss: 0.3873, Val Avg Corr: 0.8077
Epoch [3/20], Step 22500, Train Loss: 0.4625, Val Avg Corr: 0.8211
Epoch [3/20], Step 23000, Train Loss: 0.3721, Val Avg Corr: 0.8213
Epoch [3/20], Step 23500, Train Loss: 0.2441, Val Avg Corr: 0.8120
Epoch [3/20], Step 24000, Train Loss: 0.3758, Val Avg Corr: 0.8158
Epoch [3/20], Step 24500, Train Loss: 0.3905, Val Avg Corr: 0.8175
Epoch [3/20], Step 25000, Train Loss: 0.2947, Val Avg Corr: 0.8187
Epoch [3/20], Step 25500, Train Loss: 0.3116, Val Avg Corr: 0.8037
Epoch [3/20], Step 26000, Train Loss: 0.2201, Val Avg Corr: 0.8104
Epoch [3/20], Step 26500, Train Loss: 0.3320, Val Avg Corr: 0.8158
Epoch [3/20], Step 27000, Train Loss: 0.3440, Val Avg Corr: 0.8080
Epoch [3/20], Step 27500, Train Loss: 0.2992, Val Avg Corr: 0.8147
Epoch [3/20], Step 28000, Train Loss: 0.3325, Val Avg Corr: 0.8076
Epoch [3/20], Step 28500, Train Loss: 0.3206, Val Avg Corr: 0.8152
Epoch [3/20], Step 29000, Train Loss: 0.2415, Val Avg Corr: 0.8098
Epoch [3/20], Step 29500, Train Loss: 0.3083, Val Avg Corr: 0.8133
Epoch [3/20], Step 30000, Train Loss: 0.2375, Val Avg Corr: 0.8143
Epoch [3/20], Step 30500, Train Loss: 0.3307, Val Avg Corr: 0.8202
Epoch [3/20], Step 31000, Train Loss: 0.3431, Val Avg Corr: 0.8194
Epoch [3/20], Step 31500, Train Loss: 0.2978, Val Avg Corr: 0.8183
Epoch [3/20], Step 32000, Train Loss: 0.3296, Val Avg Corr: 0.8137
Epoch [3/20], Step 32500, Train Loss: 0.3037, Val Avg Corr: 0.8038
Epoch [3/20], Step 33000, Train Loss: 0.2925, Val Avg Corr: 0.8109
Epoch [3/20], Step 33500, Train Loss: 0.2710, Val Avg Corr: 0.8184
Epoch [3/20], Step 34000, Train Loss: 0.2937, Val Avg Corr: 0.8150
Epoch [3/20], Step 34500, Train Loss: 0.2789, Val Avg Corr: 0.8114
Epoch [3/20], Step 35000, Train Loss: 0.3536, Val Avg Corr: 0.8149
Epoch [3/20], Step 35500, Train Loss: 0.3042, Val Avg Corr: 0.8149
Epoch [3/20], Step 36000, Train Loss: 0.2531, Val Avg Corr: 0.8269
  >>> New best validation model saved with Avg Corr: 0.8269 <<<
Epoch [3/20], Step 36500, Train Loss: 0.2768, Val Avg Corr: 0.8067
Epoch [3/20], Step 37000, Train Loss: 0.2068, Val Avg Corr: 0.8159
Epoch [3/20], Step 37500, Train Loss: 0.4174, Val Avg Corr: 0.8187
Epoch [3/20], Step 38000, Train Loss: 0.3299, Val Avg Corr: 0.8186
Epoch [3/20], Step 38500, Train Loss: 0.3262, Val Avg Corr: 0.8106
Epoch [3/20], Step 39000, Train Loss: 0.3735, Val Avg Corr: 0.8103
Epoch [3/20], Step 39500, Train Loss: 0.3545, Val Avg Corr: 0.8139
Epoch [3/20], Step 40000, Train Loss: 0.3498, Val Avg Corr: 0.8117
Epoch [3/20], Step 40500, Train Loss: 0.3662, Val Avg Corr: 0.8068
Epoch [3/20], Step 41000, Train Loss: 0.2562, Val Avg Corr: 0.8148
Trial change detected: 1426 -> 1429, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.2974, Val Avg Corr: 0.8174
Epoch [3/20], Step 42000, Train Loss: 0.3645, Val Avg Corr: 0.8170
Epoch [3/20], Step 42500, Train Loss: 0.3315, Val Avg Corr: 0.8124
Epoch [3/20], Step 43000, Train Loss: 0.3398, Val Avg Corr: 0.8138
Epoch [3/20], Step 43500, Train Loss: 0.3374, Val Avg Corr: 0.8132
Epoch [3/20], Step 44000, Train Loss: 0.2872, Val Avg Corr: 0.8198
Epoch [3/20], Step 44500, Train Loss: 0.2923, Val Avg Corr: 0.8118
Epoch [3/20], Step 45000, Train Loss: 0.3333, Val Avg Corr: 0.8163
Epoch [3/20], Step 45500, Train Loss: 0.2776, Val Avg Corr: 0.8112
Epoch [3/20], Step 46000, Train Loss: 0.2895, Val Avg Corr: 0.8092
Epoch [3/20], Step 46500, Train Loss: 0.4526, Val Avg Corr: 0.8110
Epoch [3/20], Step 47000, Train Loss: 0.2857, Val Avg Corr: 0.8141
Epoch [3/20], Step 47500, Train Loss: 0.2034, Val Avg Corr: 0.8244
Epoch [3/20], Step 48000, Train Loss: 0.3344, Val Avg Corr: 0.8275
  >>> New best validation model saved with Avg Corr: 0.8275 <<<
Epoch [3/20], Step 48500, Train Loss: 0.2612, Val Avg Corr: 0.8132
Epoch [3/20], Step 49000, Train Loss: 0.3522, Val Avg Corr: 0.8176
Epoch [3/20], Step 49500, Train Loss: 0.3536, Val Avg Corr: 0.8194
Epoch [3/20], Step 50000, Train Loss: 0.2958, Val Avg Corr: 0.8167
Epoch [3/20], Step 50500, Train Loss: 0.3484, Val Avg Corr: 0.8251
Epoch [3/20], Step 51000, Train Loss: 0.2949, Val Avg Corr: 0.8218
Epoch [3/20], Step 51500, Train Loss: 0.3039, Val Avg Corr: 0.8226
Epoch [3/20], Step 52000, Train Loss: 0.3456, Val Avg Corr: 0.8237
Epoch [3/20], Step 52500, Train Loss: 0.3127, Val Avg Corr: 0.8232
Epoch [3/20], Step 53000, Train Loss: 0.3504, Val Avg Corr: 0.8199
Epoch [3/20], Step 53500, Train Loss: 0.3519, Val Avg Corr: 0.8294
  >>> New best validation model saved with Avg Corr: 0.8294 <<<
Epoch [3/20], Step 54000, Train Loss: 0.3305, Val Avg Corr: 0.8156
Epoch [3/20], Step 54500, Train Loss: 0.3293, Val Avg Corr: 0.8243
Epoch [3/20], Step 55000, Train Loss: 0.3953, Val Avg Corr: 0.8176
Epoch [3/20], Step 55500, Train Loss: 0.3005, Val Avg Corr: 0.8235
Epoch [3/20], Step 56000, Train Loss: 0.3346, Val Avg Corr: 0.8262
Epoch [3/20], Step 56500, Train Loss: 0.3346, Val Avg Corr: 0.8272
Epoch [3/20], Step 57000, Train Loss: 0.3445, Val Avg Corr: 0.8240
Epoch [3/20], Step 57500, Train Loss: 0.2578, Val Avg Corr: 0.8230
Epoch [3/20], Step 58000, Train Loss: 0.2918, Val Avg Corr: 0.8211
Epoch [3/20], Step 58500, Train Loss: 0.3304, Val Avg Corr: 0.8266
Epoch [3/20], Step 59000, Train Loss: 0.3139, Val Avg Corr: 0.8293
Epoch [3/20], Step 59500, Train Loss: 0.3009, Val Avg Corr: 0.8186
Epoch [3/20], Step 60000, Train Loss: 0.3469, Val Avg Corr: 0.8235
Epoch [3/20], Step 60500, Train Loss: 0.2647, Val Avg Corr: 0.8110
Epoch [3/20], Step 61000, Train Loss: 0.2100, Val Avg Corr: 0.8229
Epoch [3/20], Step 61500, Train Loss: 0.3675, Val Avg Corr: 0.8229
Trial change detected: 2147 -> 2148, resetting states
Epoch [3/20], Step 62000, Train Loss: 0.2735, Val Avg Corr: 0.8279
Epoch [3/20], Step 62500, Train Loss: 0.3167, Val Avg Corr: 0.8298
  >>> New best validation model saved with Avg Corr: 0.8298 <<<
Epoch [3/20], Step 63000, Train Loss: 0.2598, Val Avg Corr: 0.8276
Epoch [3/20], Step 63500, Train Loss: 0.3285, Val Avg Corr: 0.8268
Epoch [3/20], Step 64000, Train Loss: 0.3282, Val Avg Corr: 0.8248
Epoch [3/20], Step 64500, Train Loss: 0.3476, Val Avg Corr: 0.8210
Epoch [3/20], Step 65000, Train Loss: 0.2760, Val Avg Corr: 0.8124
Epoch [3/20], Step 65500, Train Loss: 0.2966, Val Avg Corr: 0.8173
Epoch [4/20], Step 500, Train Loss: 0.3387, Val Avg Corr: 0.8178
Epoch [4/20], Step 1000, Train Loss: 0.3467, Val Avg Corr: 0.8187
Epoch [4/20], Step 1500, Train Loss: 0.3773, Val Avg Corr: 0.8250
Epoch [4/20], Step 2000, Train Loss: 0.2663, Val Avg Corr: 0.8263
Epoch [4/20], Step 2500, Train Loss: 0.2207, Val Avg Corr: 0.8188
Epoch [4/20], Step 3000, Train Loss: 0.3627, Val Avg Corr: 0.8275
Epoch [4/20], Step 3500, Train Loss: 0.3309, Val Avg Corr: 0.8247
Epoch [4/20], Step 4000, Train Loss: 0.2674, Val Avg Corr: 0.8247
Epoch [4/20], Step 4500, Train Loss: 0.3875, Val Avg Corr: 0.8255
Epoch [4/20], Step 5000, Train Loss: 0.2653, Val Avg Corr: 0.8234
Epoch [4/20], Step 5500, Train Loss: 0.3471, Val Avg Corr: 0.8291
Epoch [4/20], Step 6000, Train Loss: 0.2105, Val Avg Corr: 0.8225
Epoch [4/20], Step 6500, Train Loss: 0.3386, Val Avg Corr: 0.8216
Epoch [4/20], Step 7000, Train Loss: 0.3109, Val Avg Corr: 0.8209
Epoch [4/20], Step 7500, Train Loss: 0.3320, Val Avg Corr: 0.8210
Epoch [4/20], Step 8000, Train Loss: 0.2558, Val Avg Corr: 0.8146
Epoch [4/20], Step 8500, Train Loss: 0.4512, Val Avg Corr: 0.8238
Epoch [4/20], Step 9000, Train Loss: 0.3016, Val Avg Corr: 0.8307
  >>> New best validation model saved with Avg Corr: 0.8307 <<<
Epoch [4/20], Step 9500, Train Loss: 0.2673, Val Avg Corr: 0.8225
Epoch [4/20], Step 10000, Train Loss: 0.3250, Val Avg Corr: 0.8239
Epoch [4/20], Step 10500, Train Loss: 0.2262, Val Avg Corr: 0.8228
Epoch [4/20], Step 11000, Train Loss: 0.2818, Val Avg Corr: 0.8258
Epoch [4/20], Step 11500, Train Loss: 0.2850, Val Avg Corr: 0.8216
Epoch [4/20], Step 12000, Train Loss: 0.2764, Val Avg Corr: 0.8213
Epoch [4/20], Step 12500, Train Loss: 0.2985, Val Avg Corr: 0.8212
Epoch [4/20], Step 13000, Train Loss: 0.2819, Val Avg Corr: 0.8194
Epoch [4/20], Step 13500, Train Loss: 0.3248, Val Avg Corr: 0.8220
Epoch [4/20], Step 14000, Train Loss: 0.3034, Val Avg Corr: 0.8270
Epoch [4/20], Step 14500, Train Loss: 0.2466, Val Avg Corr: 0.8253
Epoch [4/20], Step 15000, Train Loss: 0.3641, Val Avg Corr: 0.8266
Epoch [4/20], Step 15500, Train Loss: 0.3519, Val Avg Corr: 0.8282
Epoch [4/20], Step 16000, Train Loss: 0.3410, Val Avg Corr: 0.8267
Epoch [4/20], Step 16500, Train Loss: 0.4145, Val Avg Corr: 0.8254
Epoch [4/20], Step 17000, Train Loss: 0.2820, Val Avg Corr: 0.8255
Epoch [4/20], Step 17500, Train Loss: 0.2520, Val Avg Corr: 0.8284
Epoch [4/20], Step 18000, Train Loss: 0.3323, Val Avg Corr: 0.8245
Epoch [4/20], Step 18500, Train Loss: 0.3541, Val Avg Corr: 0.8345
  >>> New best validation model saved with Avg Corr: 0.8345 <<<
Epoch [4/20], Step 19000, Train Loss: 0.3503, Val Avg Corr: 0.8264
Epoch [4/20], Step 19500, Train Loss: 0.3054, Val Avg Corr: 0.8239
Epoch [4/20], Step 20000, Train Loss: 0.3262, Val Avg Corr: 0.8238
Epoch [4/20], Step 20500, Train Loss: 0.2623, Val Avg Corr: 0.8284
Trial change detected: 713 -> 715, resetting states
Epoch [4/20], Step 21000, Train Loss: 0.2311, Val Avg Corr: 0.8289
Epoch [4/20], Step 21500, Train Loss: 0.3175, Val Avg Corr: 0.8280
Epoch [4/20], Step 22000, Train Loss: 0.3762, Val Avg Corr: 0.8264
Epoch [4/20], Step 22500, Train Loss: 0.4167, Val Avg Corr: 0.8309
Epoch [4/20], Step 23000, Train Loss: 0.3387, Val Avg Corr: 0.8331
Epoch [4/20], Step 23500, Train Loss: 0.2229, Val Avg Corr: 0.8263
Epoch [4/20], Step 24000, Train Loss: 0.3498, Val Avg Corr: 0.8308
Epoch [4/20], Step 24500, Train Loss: 0.3739, Val Avg Corr: 0.8335
Epoch [4/20], Step 25000, Train Loss: 0.2865, Val Avg Corr: 0.8307
Epoch [4/20], Step 25500, Train Loss: 0.2949, Val Avg Corr: 0.8174
Epoch [4/20], Step 26000, Train Loss: 0.2053, Val Avg Corr: 0.8256
Epoch [4/20], Step 26500, Train Loss: 0.2990, Val Avg Corr: 0.8263
Epoch [4/20], Step 27000, Train Loss: 0.3162, Val Avg Corr: 0.8285
Epoch [4/20], Step 27500, Train Loss: 0.2782, Val Avg Corr: 0.8304
Epoch [4/20], Step 28000, Train Loss: 0.3117, Val Avg Corr: 0.8275
Epoch [4/20], Step 28500, Train Loss: 0.2935, Val Avg Corr: 0.8280
Epoch [4/20], Step 29000, Train Loss: 0.2372, Val Avg Corr: 0.8224
Epoch [4/20], Step 29500, Train Loss: 0.2925, Val Avg Corr: 0.8317
Epoch [4/20], Step 30000, Train Loss: 0.2187, Val Avg Corr: 0.8236
Epoch [4/20], Step 30500, Train Loss: 0.3238, Val Avg Corr: 0.8296
Epoch [4/20], Step 31000, Train Loss: 0.3195, Val Avg Corr: 0.8288
Epoch [4/20], Step 31500, Train Loss: 0.2828, Val Avg Corr: 0.8308
Epoch [4/20], Step 32000, Train Loss: 0.3148, Val Avg Corr: 0.8257
Epoch [4/20], Step 32500, Train Loss: 0.2947, Val Avg Corr: 0.8185
Epoch [4/20], Step 33000, Train Loss: 0.2768, Val Avg Corr: 0.8314
Epoch [4/20], Step 33500, Train Loss: 0.2468, Val Avg Corr: 0.8354
  >>> New best validation model saved with Avg Corr: 0.8354 <<<
Epoch [4/20], Step 34000, Train Loss: 0.2794, Val Avg Corr: 0.8278
Epoch [4/20], Step 34500, Train Loss: 0.2651, Val Avg Corr: 0.8282
Epoch [4/20], Step 35000, Train Loss: 0.3265, Val Avg Corr: 0.8326
Epoch [4/20], Step 35500, Train Loss: 0.2999, Val Avg Corr: 0.8285
Epoch [4/20], Step 36000, Train Loss: 0.2501, Val Avg Corr: 0.8331
Epoch [4/20], Step 36500, Train Loss: 0.2579, Val Avg Corr: 0.8230
Epoch [4/20], Step 37000, Train Loss: 0.2084, Val Avg Corr: 0.8284
Epoch [4/20], Step 37500, Train Loss: 0.3940, Val Avg Corr: 0.8236
Epoch [4/20], Step 38000, Train Loss: 0.3100, Val Avg Corr: 0.8298
Epoch [4/20], Step 38500, Train Loss: 0.2971, Val Avg Corr: 0.8250
Epoch [4/20], Step 39000, Train Loss: 0.3398, Val Avg Corr: 0.8247
Epoch [4/20], Step 39500, Train Loss: 0.3212, Val Avg Corr: 0.8219
Epoch [4/20], Step 40000, Train Loss: 0.3285, Val Avg Corr: 0.8305
Epoch [4/20], Step 40500, Train Loss: 0.3268, Val Avg Corr: 0.8239
Epoch [4/20], Step 41000, Train Loss: 0.2361, Val Avg Corr: 0.8234
Trial change detected: 1426 -> 1429, resetting states
Epoch [4/20], Step 41500, Train Loss: 0.2784, Val Avg Corr: 0.8282
Epoch [4/20], Step 42000, Train Loss: 0.3369, Val Avg Corr: 0.8255
Epoch [4/20], Step 42500, Train Loss: 0.3229, Val Avg Corr: 0.8213
Epoch [4/20], Step 43000, Train Loss: 0.3413, Val Avg Corr: 0.8297
Epoch [4/20], Step 43500, Train Loss: 0.3122, Val Avg Corr: 0.8292
Epoch [4/20], Step 44000, Train Loss: 0.2779, Val Avg Corr: 0.8292
Epoch [4/20], Step 44500, Train Loss: 0.2815, Val Avg Corr: 0.8309
Epoch [4/20], Step 45000, Train Loss: 0.3309, Val Avg Corr: 0.8292
Epoch [4/20], Step 45500, Train Loss: 0.2614, Val Avg Corr: 0.8266
Epoch [4/20], Step 46000, Train Loss: 0.2801, Val Avg Corr: 0.8239
Epoch [4/20], Step 46500, Train Loss: 0.4377, Val Avg Corr: 0.8174
Epoch [4/20], Step 47000, Train Loss: 0.2672, Val Avg Corr: 0.8255
Epoch [4/20], Step 47500, Train Loss: 0.1828, Val Avg Corr: 0.8270
Epoch [4/20], Step 48000, Train Loss: 0.3047, Val Avg Corr: 0.8365
  >>> New best validation model saved with Avg Corr: 0.8365 <<<
Epoch [4/20], Step 48500, Train Loss: 0.2488, Val Avg Corr: 0.8226
Epoch [4/20], Step 49000, Train Loss: 0.3388, Val Avg Corr: 0.8280
Epoch [4/20], Step 49500, Train Loss: 0.3352, Val Avg Corr: 0.8287
Epoch [4/20], Step 50000, Train Loss: 0.2838, Val Avg Corr: 0.8279
Epoch [4/20], Step 50500, Train Loss: 0.3295, Val Avg Corr: 0.8295
Epoch [4/20], Step 51000, Train Loss: 0.2938, Val Avg Corr: 0.8271
Epoch [4/20], Step 51500, Train Loss: 0.2766, Val Avg Corr: 0.8265
Epoch [4/20], Step 52000, Train Loss: 0.3228, Val Avg Corr: 0.8335
Epoch [4/20], Step 52500, Train Loss: 0.2934, Val Avg Corr: 0.8278
Epoch [4/20], Step 53000, Train Loss: 0.3297, Val Avg Corr: 0.8302
Epoch [4/20], Step 53500, Train Loss: 0.3219, Val Avg Corr: 0.8349
Epoch [4/20], Step 54000, Train Loss: 0.3257, Val Avg Corr: 0.8327
Epoch [4/20], Step 54500, Train Loss: 0.3175, Val Avg Corr: 0.8318
Epoch [4/20], Step 55000, Train Loss: 0.3565, Val Avg Corr: 0.8322
Epoch [4/20], Step 55500, Train Loss: 0.2758, Val Avg Corr: 0.8339
Epoch [4/20], Step 56000, Train Loss: 0.3133, Val Avg Corr: 0.8377
  >>> New best validation model saved with Avg Corr: 0.8377 <<<
Epoch [4/20], Step 56500, Train Loss: 0.3276, Val Avg Corr: 0.8288
Epoch [4/20], Step 57000, Train Loss: 0.3228, Val Avg Corr: 0.8352
Epoch [4/20], Step 57500, Train Loss: 0.2396, Val Avg Corr: 0.8393
  >>> New best validation model saved with Avg Corr: 0.8393 <<<
Epoch [4/20], Step 58000, Train Loss: 0.2673, Val Avg Corr: 0.8375
Epoch [4/20], Step 58500, Train Loss: 0.3073, Val Avg Corr: 0.8384
Epoch [4/20], Step 59000, Train Loss: 0.2994, Val Avg Corr: 0.8374
Epoch [4/20], Step 59500, Train Loss: 0.2811, Val Avg Corr: 0.8303
Epoch [4/20], Step 60000, Train Loss: 0.3190, Val Avg Corr: 0.8282
Epoch [4/20], Step 60500, Train Loss: 0.2537, Val Avg Corr: 0.8236
Epoch [4/20], Step 61000, Train Loss: 0.1835, Val Avg Corr: 0.8320
Epoch [4/20], Step 61500, Train Loss: 0.3332, Val Avg Corr: 0.8396
  >>> New best validation model saved with Avg Corr: 0.8396 <<<
Trial change detected: 2147 -> 2148, resetting states
Epoch [4/20], Step 62000, Train Loss: 0.2614, Val Avg Corr: 0.8363
Epoch [4/20], Step 62500, Train Loss: 0.2953, Val Avg Corr: 0.8389
Epoch [4/20], Step 63000, Train Loss: 0.2537, Val Avg Corr: 0.8410
  >>> New best validation model saved with Avg Corr: 0.8410 <<<
Epoch [4/20], Step 63500, Train Loss: 0.3028, Val Avg Corr: 0.8398
Epoch [4/20], Step 64000, Train Loss: 0.3231, Val Avg Corr: 0.8427
  >>> New best validation model saved with Avg Corr: 0.8427 <<<
Epoch [4/20], Step 64500, Train Loss: 0.3164, Val Avg Corr: 0.8316
Epoch [4/20], Step 65000, Train Loss: 0.2681, Val Avg Corr: 0.8267
Epoch [4/20], Step 65500, Train Loss: 0.2931, Val Avg Corr: 0.8298
Epoch [5/20], Step 500, Train Loss: 0.3149, Val Avg Corr: 0.8380
Epoch [5/20], Step 1000, Train Loss: 0.3269, Val Avg Corr: 0.8367
Epoch [5/20], Step 1500, Train Loss: 0.3741, Val Avg Corr: 0.8346
Epoch [5/20], Step 2000, Train Loss: 0.2628, Val Avg Corr: 0.8365
Epoch [5/20], Step 2500, Train Loss: 0.2101, Val Avg Corr: 0.8303
Epoch [5/20], Step 3000, Train Loss: 0.3423, Val Avg Corr: 0.8348
Epoch [5/20], Step 3500, Train Loss: 0.3180, Val Avg Corr: 0.8313
Epoch [5/20], Step 4000, Train Loss: 0.2434, Val Avg Corr: 0.8335
Epoch [5/20], Step 4500, Train Loss: 0.3564, Val Avg Corr: 0.8336
Epoch [5/20], Step 5000, Train Loss: 0.2380, Val Avg Corr: 0.8331
Epoch [5/20], Step 5500, Train Loss: 0.3323, Val Avg Corr: 0.8352
Epoch [5/20], Step 6000, Train Loss: 0.2195, Val Avg Corr: 0.8312
Epoch [5/20], Step 6500, Train Loss: 0.3088, Val Avg Corr: 0.8342
Epoch [5/20], Step 7000, Train Loss: 0.3005, Val Avg Corr: 0.8282
Epoch [5/20], Step 7500, Train Loss: 0.3010, Val Avg Corr: 0.8253
Epoch [5/20], Step 8000, Train Loss: 0.2399, Val Avg Corr: 0.8283
Epoch [5/20], Step 8500, Train Loss: 0.4320, Val Avg Corr: 0.8320
Epoch [5/20], Step 9000, Train Loss: 0.2877, Val Avg Corr: 0.8345
Epoch [5/20], Step 9500, Train Loss: 0.2557, Val Avg Corr: 0.8353
Epoch [5/20], Step 10000, Train Loss: 0.3049, Val Avg Corr: 0.8343
Epoch [5/20], Step 10500, Train Loss: 0.2193, Val Avg Corr: 0.8298
Epoch [5/20], Step 11000, Train Loss: 0.2658, Val Avg Corr: 0.8277
Epoch [5/20], Step 11500, Train Loss: 0.2690, Val Avg Corr: 0.8311
Epoch [5/20], Step 12000, Train Loss: 0.2643, Val Avg Corr: 0.8322
Epoch [5/20], Step 12500, Train Loss: 0.2961, Val Avg Corr: 0.8316
Epoch [5/20], Step 13000, Train Loss: 0.2679, Val Avg Corr: 0.8353
Epoch [5/20], Step 13500, Train Loss: 0.3065, Val Avg Corr: 0.8378
Epoch [5/20], Step 14000, Train Loss: 0.3041, Val Avg Corr: 0.8377
Epoch [5/20], Step 14500, Train Loss: 0.2438, Val Avg Corr: 0.8393
Epoch [5/20], Step 15000, Train Loss: 0.3523, Val Avg Corr: 0.8371
Epoch [5/20], Step 15500, Train Loss: 0.3383, Val Avg Corr: 0.8401
Epoch [5/20], Step 16000, Train Loss: 0.3206, Val Avg Corr: 0.8369
Epoch [5/20], Step 16500, Train Loss: 0.3983, Val Avg Corr: 0.8367
Epoch [5/20], Step 17000, Train Loss: 0.2649, Val Avg Corr: 0.8355
Epoch [5/20], Step 17500, Train Loss: 0.2361, Val Avg Corr: 0.8386
Epoch [5/20], Step 18000, Train Loss: 0.3197, Val Avg Corr: 0.8364
Epoch [5/20], Step 18500, Train Loss: 0.3248, Val Avg Corr: 0.8378
Epoch [5/20], Step 19000, Train Loss: 0.3526, Val Avg Corr: 0.8339
Epoch [5/20], Step 19500, Train Loss: 0.2884, Val Avg Corr: 0.8361
Epoch [5/20], Step 20000, Train Loss: 0.3058, Val Avg Corr: 0.8332
Epoch [5/20], Step 20500, Train Loss: 0.2617, Val Avg Corr: 0.8384
Trial change detected: 713 -> 715, resetting states
Epoch [5/20], Step 21000, Train Loss: 0.2186, Val Avg Corr: 0.8401
Epoch [5/20], Step 21500, Train Loss: 0.3078, Val Avg Corr: 0.8407
Epoch [5/20], Step 22000, Train Loss: 0.3486, Val Avg Corr: 0.8333
Epoch [5/20], Step 22500, Train Loss: 0.4072, Val Avg Corr: 0.8338
Epoch [5/20], Step 23000, Train Loss: 0.3200, Val Avg Corr: 0.8380
Epoch [5/20], Step 23500, Train Loss: 0.2137, Val Avg Corr: 0.8352
Early stopping triggered after 23500 steps in epoch 5.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8427
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8510, Y=0.8124, Avg=0.8317

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 8) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    0.0    2.0    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    0.0    2.0    2.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.0664, Val Avg Corr: 0.0659
  >>> New best validation model saved with Avg Corr: 0.0659 <<<
Epoch [1/20], Step 1000, Train Loss: 1.0927, Val Avg Corr: 0.1189
  >>> New best validation model saved with Avg Corr: 0.1189 <<<
Epoch [1/20], Step 1500, Train Loss: 1.0188, Val Avg Corr: 0.1171
Epoch [1/20], Step 2000, Train Loss: 1.1155, Val Avg Corr: 0.1314
  >>> New best validation model saved with Avg Corr: 0.1314 <<<
Epoch [1/20], Step 2500, Train Loss: 0.8692, Val Avg Corr: 0.1444
  >>> New best validation model saved with Avg Corr: 0.1444 <<<
Epoch [1/20], Step 3000, Train Loss: 1.1711, Val Avg Corr: 0.1534
  >>> New best validation model saved with Avg Corr: 0.1534 <<<
Epoch [1/20], Step 3500, Train Loss: 0.8760, Val Avg Corr: 0.1756
  >>> New best validation model saved with Avg Corr: 0.1756 <<<
Epoch [1/20], Step 4000, Train Loss: 0.8615, Val Avg Corr: 0.1793
  >>> New best validation model saved with Avg Corr: 0.1793 <<<
Epoch [1/20], Step 4500, Train Loss: 1.1050, Val Avg Corr: 0.1813
  >>> New best validation model saved with Avg Corr: 0.1813 <<<
Epoch [1/20], Step 5000, Train Loss: 0.9908, Val Avg Corr: 0.1905
  >>> New best validation model saved with Avg Corr: 0.1905 <<<
Epoch [1/20], Step 5500, Train Loss: 0.8812, Val Avg Corr: 0.3116
  >>> New best validation model saved with Avg Corr: 0.3116 <<<
Epoch [1/20], Step 6000, Train Loss: 1.0087, Val Avg Corr: 0.3056
Epoch [1/20], Step 6500, Train Loss: 0.7298, Val Avg Corr: 0.2719
Epoch [1/20], Step 7000, Train Loss: 0.8303, Val Avg Corr: 0.3109
Epoch [1/20], Step 7500, Train Loss: 0.7622, Val Avg Corr: 0.3491
  >>> New best validation model saved with Avg Corr: 0.3491 <<<
Epoch [1/20], Step 8000, Train Loss: 0.7966, Val Avg Corr: 0.3500
  >>> New best validation model saved with Avg Corr: 0.3500 <<<
Epoch [1/20], Step 8500, Train Loss: 0.8745, Val Avg Corr: 0.3739
  >>> New best validation model saved with Avg Corr: 0.3739 <<<
Epoch [1/20], Step 9000, Train Loss: 0.9156, Val Avg Corr: 0.4081
  >>> New best validation model saved with Avg Corr: 0.4081 <<<
Epoch [1/20], Step 9500, Train Loss: 0.6901, Val Avg Corr: 0.3622
Epoch [1/20], Step 10000, Train Loss: 0.7519, Val Avg Corr: 0.3288
Epoch [1/20], Step 10500, Train Loss: 0.6239, Val Avg Corr: 0.3511
Epoch [1/20], Step 11000, Train Loss: 0.7639, Val Avg Corr: 0.3902
Epoch [1/20], Step 11500, Train Loss: 0.6746, Val Avg Corr: 0.4465
  >>> New best validation model saved with Avg Corr: 0.4465 <<<
Epoch [1/20], Step 12000, Train Loss: 0.4964, Val Avg Corr: 0.4513
  >>> New best validation model saved with Avg Corr: 0.4513 <<<
Epoch [1/20], Step 12500, Train Loss: 0.7015, Val Avg Corr: 0.4874
  >>> New best validation model saved with Avg Corr: 0.4874 <<<
Epoch [1/20], Step 13000, Train Loss: 0.8404, Val Avg Corr: 0.5245
  >>> New best validation model saved with Avg Corr: 0.5245 <<<
Epoch [1/20], Step 13500, Train Loss: 0.8823, Val Avg Corr: 0.5216
Epoch [1/20], Step 14000, Train Loss: 0.7135, Val Avg Corr: 0.5272
  >>> New best validation model saved with Avg Corr: 0.5272 <<<
Epoch [1/20], Step 14500, Train Loss: 0.7816, Val Avg Corr: 0.5458
  >>> New best validation model saved with Avg Corr: 0.5458 <<<
Epoch [1/20], Step 15000, Train Loss: 0.7817, Val Avg Corr: 0.5637
  >>> New best validation model saved with Avg Corr: 0.5637 <<<
Epoch [1/20], Step 15500, Train Loss: 0.6831, Val Avg Corr: 0.5575
Epoch [1/20], Step 16000, Train Loss: 0.5391, Val Avg Corr: 0.5818
  >>> New best validation model saved with Avg Corr: 0.5818 <<<
Epoch [1/20], Step 16500, Train Loss: 0.7816, Val Avg Corr: 0.5996
  >>> New best validation model saved with Avg Corr: 0.5996 <<<
Epoch [1/20], Step 17000, Train Loss: 0.6974, Val Avg Corr: 0.5866
Epoch [1/20], Step 17500, Train Loss: 0.4732, Val Avg Corr: 0.5786
Epoch [1/20], Step 18000, Train Loss: 0.7218, Val Avg Corr: 0.5964
Epoch [1/20], Step 18500, Train Loss: 0.6340, Val Avg Corr: 0.6049
  >>> New best validation model saved with Avg Corr: 0.6049 <<<
Epoch [1/20], Step 19000, Train Loss: 0.6896, Val Avg Corr: 0.6131
  >>> New best validation model saved with Avg Corr: 0.6131 <<<
Epoch [1/20], Step 19500, Train Loss: 0.5841, Val Avg Corr: 0.6197
  >>> New best validation model saved with Avg Corr: 0.6197 <<<
Epoch [1/20], Step 20000, Train Loss: 0.5728, Val Avg Corr: 0.6351
  >>> New best validation model saved with Avg Corr: 0.6351 <<<
Epoch [1/20], Step 20500, Train Loss: 0.4838, Val Avg Corr: 0.6331
Trial change detected: 722 -> 723, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.4130, Val Avg Corr: 0.6458
  >>> New best validation model saved with Avg Corr: 0.6458 <<<
Epoch [1/20], Step 21500, Train Loss: 0.5620, Val Avg Corr: 0.6477
  >>> New best validation model saved with Avg Corr: 0.6477 <<<
Epoch [1/20], Step 22000, Train Loss: 0.6479, Val Avg Corr: 0.6275
Epoch [1/20], Step 22500, Train Loss: 0.5760, Val Avg Corr: 0.6383
Epoch [1/20], Step 23000, Train Loss: 0.5744, Val Avg Corr: 0.6451
Epoch [1/20], Step 23500, Train Loss: 0.4289, Val Avg Corr: 0.6520
  >>> New best validation model saved with Avg Corr: 0.6520 <<<
Epoch [1/20], Step 24000, Train Loss: 0.5405, Val Avg Corr: 0.6697
  >>> New best validation model saved with Avg Corr: 0.6697 <<<
Epoch [1/20], Step 24500, Train Loss: 0.6398, Val Avg Corr: 0.6573
Epoch [1/20], Step 25000, Train Loss: 0.4869, Val Avg Corr: 0.6740
  >>> New best validation model saved with Avg Corr: 0.6740 <<<
Epoch [1/20], Step 25500, Train Loss: 0.4740, Val Avg Corr: 0.6929
  >>> New best validation model saved with Avg Corr: 0.6929 <<<
Epoch [1/20], Step 26000, Train Loss: 0.4380, Val Avg Corr: 0.6833
Epoch [1/20], Step 26500, Train Loss: 0.3863, Val Avg Corr: 0.6806
Epoch [1/20], Step 27000, Train Loss: 0.5303, Val Avg Corr: 0.6942
  >>> New best validation model saved with Avg Corr: 0.6942 <<<
Epoch [1/20], Step 27500, Train Loss: 0.3752, Val Avg Corr: 0.6933
Epoch [1/20], Step 28000, Train Loss: 0.5459, Val Avg Corr: 0.6953
  >>> New best validation model saved with Avg Corr: 0.6953 <<<
Epoch [1/20], Step 28500, Train Loss: 0.5078, Val Avg Corr: 0.6921
Epoch [1/20], Step 29000, Train Loss: 0.4295, Val Avg Corr: 0.7066
  >>> New best validation model saved with Avg Corr: 0.7066 <<<
Epoch [1/20], Step 29500, Train Loss: 0.4004, Val Avg Corr: 0.7001
Epoch [1/20], Step 30000, Train Loss: 0.3554, Val Avg Corr: 0.7124
  >>> New best validation model saved with Avg Corr: 0.7124 <<<
Epoch [1/20], Step 30500, Train Loss: 0.4805, Val Avg Corr: 0.7107
Epoch [1/20], Step 31000, Train Loss: 0.5264, Val Avg Corr: 0.7145
  >>> New best validation model saved with Avg Corr: 0.7145 <<<
Epoch [1/20], Step 31500, Train Loss: 0.4795, Val Avg Corr: 0.7167
  >>> New best validation model saved with Avg Corr: 0.7167 <<<
Epoch [1/20], Step 32000, Train Loss: 0.5544, Val Avg Corr: 0.7194
  >>> New best validation model saved with Avg Corr: 0.7194 <<<
Epoch [1/20], Step 32500, Train Loss: 0.4419, Val Avg Corr: 0.7282
  >>> New best validation model saved with Avg Corr: 0.7282 <<<
Epoch [1/20], Step 33000, Train Loss: 0.3651, Val Avg Corr: 0.7218
Epoch [1/20], Step 33500, Train Loss: 0.4173, Val Avg Corr: 0.7268
Epoch [1/20], Step 34000, Train Loss: 0.4485, Val Avg Corr: 0.7227
Epoch [1/20], Step 34500, Train Loss: 0.4044, Val Avg Corr: 0.7241
Epoch [1/20], Step 35000, Train Loss: 0.3298, Val Avg Corr: 0.7294
  >>> New best validation model saved with Avg Corr: 0.7294 <<<
Epoch [1/20], Step 35500, Train Loss: 0.3770, Val Avg Corr: 0.7274
Epoch [1/20], Step 36000, Train Loss: 0.3913, Val Avg Corr: 0.7267
Epoch [1/20], Step 36500, Train Loss: 0.3540, Val Avg Corr: 0.7294
Epoch [1/20], Step 37000, Train Loss: 0.6090, Val Avg Corr: 0.7374
  >>> New best validation model saved with Avg Corr: 0.7374 <<<
Epoch [1/20], Step 37500, Train Loss: 0.5553, Val Avg Corr: 0.7282
Epoch [1/20], Step 38000, Train Loss: 0.3944, Val Avg Corr: 0.7349
Epoch [1/20], Step 38500, Train Loss: 0.4729, Val Avg Corr: 0.7288
Epoch [1/20], Step 39000, Train Loss: 0.4520, Val Avg Corr: 0.7411
  >>> New best validation model saved with Avg Corr: 0.7411 <<<
Epoch [1/20], Step 39500, Train Loss: 0.4177, Val Avg Corr: 0.7391
Epoch [1/20], Step 40000, Train Loss: 0.5084, Val Avg Corr: 0.7403
Epoch [1/20], Step 40500, Train Loss: 0.3940, Val Avg Corr: 0.7304
Epoch [1/20], Step 41000, Train Loss: 0.2806, Val Avg Corr: 0.7336
Trial change detected: 1433 -> 1434, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.3833, Val Avg Corr: 0.7467
  >>> New best validation model saved with Avg Corr: 0.7467 <<<
Epoch [1/20], Step 42000, Train Loss: 0.4878, Val Avg Corr: 0.7386
Epoch [1/20], Step 42500, Train Loss: 0.2890, Val Avg Corr: 0.7393
Epoch [1/20], Step 43000, Train Loss: 0.4260, Val Avg Corr: 0.7496
  >>> New best validation model saved with Avg Corr: 0.7496 <<<
Epoch [1/20], Step 43500, Train Loss: 0.4567, Val Avg Corr: 0.7423
Epoch [1/20], Step 44000, Train Loss: 0.4089, Val Avg Corr: 0.7267
Epoch [1/20], Step 44500, Train Loss: 0.4562, Val Avg Corr: 0.7430
Epoch [1/20], Step 45000, Train Loss: 0.4812, Val Avg Corr: 0.7487
Epoch [1/20], Step 45500, Train Loss: 0.3755, Val Avg Corr: 0.7455
Epoch [1/20], Step 46000, Train Loss: 0.4112, Val Avg Corr: 0.7543
  >>> New best validation model saved with Avg Corr: 0.7543 <<<
Epoch [1/20], Step 46500, Train Loss: 0.4794, Val Avg Corr: 0.7599
  >>> New best validation model saved with Avg Corr: 0.7599 <<<
Epoch [1/20], Step 47000, Train Loss: 0.3256, Val Avg Corr: 0.7549
Epoch [1/20], Step 47500, Train Loss: 0.3566, Val Avg Corr: 0.7594
Epoch [1/20], Step 48000, Train Loss: 0.3444, Val Avg Corr: 0.7516
Epoch [1/20], Step 48500, Train Loss: 0.4823, Val Avg Corr: 0.7574
Epoch [1/20], Step 49000, Train Loss: 0.5089, Val Avg Corr: 0.7623
  >>> New best validation model saved with Avg Corr: 0.7623 <<<
Epoch [1/20], Step 49500, Train Loss: 0.3632, Val Avg Corr: 0.7515
Epoch [1/20], Step 50000, Train Loss: 0.3848, Val Avg Corr: 0.7643
  >>> New best validation model saved with Avg Corr: 0.7643 <<<
Epoch [1/20], Step 50500, Train Loss: 0.4081, Val Avg Corr: 0.7631
Epoch [1/20], Step 51000, Train Loss: 0.4118, Val Avg Corr: 0.7572
Epoch [1/20], Step 51500, Train Loss: 0.4295, Val Avg Corr: 0.7655
  >>> New best validation model saved with Avg Corr: 0.7655 <<<
Epoch [1/20], Step 52000, Train Loss: 0.3673, Val Avg Corr: 0.7699
  >>> New best validation model saved with Avg Corr: 0.7699 <<<
Epoch [1/20], Step 52500, Train Loss: 0.4580, Val Avg Corr: 0.7639
Epoch [1/20], Step 53000, Train Loss: 0.4542, Val Avg Corr: 0.7648
Epoch [1/20], Step 53500, Train Loss: 0.4630, Val Avg Corr: 0.7710
  >>> New best validation model saved with Avg Corr: 0.7710 <<<
Epoch [1/20], Step 54000, Train Loss: 0.4465, Val Avg Corr: 0.7552
Epoch [1/20], Step 54500, Train Loss: 0.4939, Val Avg Corr: 0.7750
  >>> New best validation model saved with Avg Corr: 0.7750 <<<
Epoch [1/20], Step 55000, Train Loss: 0.4157, Val Avg Corr: 0.7674
Epoch [1/20], Step 55500, Train Loss: 0.3795, Val Avg Corr: 0.7729
Epoch [1/20], Step 56000, Train Loss: 0.3996, Val Avg Corr: 0.7690
Epoch [1/20], Step 56500, Train Loss: 0.4403, Val Avg Corr: 0.7707
Epoch [1/20], Step 57000, Train Loss: 0.4607, Val Avg Corr: 0.7728
Epoch [1/20], Step 57500, Train Loss: 0.3897, Val Avg Corr: 0.7745
Epoch [1/20], Step 58000, Train Loss: 0.3316, Val Avg Corr: 0.7662
Epoch [1/20], Step 58500, Train Loss: 0.4445, Val Avg Corr: 0.7718
Epoch [1/20], Step 59000, Train Loss: 0.3634, Val Avg Corr: 0.7677
Epoch [1/20], Step 59500, Train Loss: 0.3717, Val Avg Corr: 0.7710
Epoch [1/20], Step 60000, Train Loss: 0.2969, Val Avg Corr: 0.7818
  >>> New best validation model saved with Avg Corr: 0.7818 <<<
Epoch [1/20], Step 60500, Train Loss: 0.4366, Val Avg Corr: 0.7641
Epoch [1/20], Step 61000, Train Loss: 0.3523, Val Avg Corr: 0.7705
Epoch [1/20], Step 61500, Train Loss: 0.4021, Val Avg Corr: 0.7728
Trial change detected: 2141 -> 2142, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3121, Val Avg Corr: 0.7730
Epoch [1/20], Step 62500, Train Loss: 0.4102, Val Avg Corr: 0.7832
  >>> New best validation model saved with Avg Corr: 0.7832 <<<
Epoch [1/20], Step 63000, Train Loss: 0.3579, Val Avg Corr: 0.7717
Epoch [1/20], Step 63500, Train Loss: 0.4445, Val Avg Corr: 0.7803
Epoch [1/20], Step 64000, Train Loss: 0.3953, Val Avg Corr: 0.7682
Epoch [1/20], Step 64500, Train Loss: 0.3479, Val Avg Corr: 0.7741
Epoch [1/20], Step 65000, Train Loss: 0.3514, Val Avg Corr: 0.7763
Epoch [1/20], Step 65500, Train Loss: 0.3939, Val Avg Corr: 0.7796
Epoch [2/20], Step 500, Train Loss: 0.3804, Val Avg Corr: 0.7822
Epoch [2/20], Step 1000, Train Loss: 0.4355, Val Avg Corr: 0.7769
Epoch [2/20], Step 1500, Train Loss: 0.4808, Val Avg Corr: 0.7805
Epoch [2/20], Step 2000, Train Loss: 0.3660, Val Avg Corr: 0.7698
Epoch [2/20], Step 2500, Train Loss: 0.3139, Val Avg Corr: 0.7802
Epoch [2/20], Step 3000, Train Loss: 0.4380, Val Avg Corr: 0.7871
  >>> New best validation model saved with Avg Corr: 0.7871 <<<
Epoch [2/20], Step 3500, Train Loss: 0.3278, Val Avg Corr: 0.7825
Epoch [2/20], Step 4000, Train Loss: 0.3253, Val Avg Corr: 0.7801
Epoch [2/20], Step 4500, Train Loss: 0.4344, Val Avg Corr: 0.7859
Epoch [2/20], Step 5000, Train Loss: 0.3952, Val Avg Corr: 0.7883
  >>> New best validation model saved with Avg Corr: 0.7883 <<<
Epoch [2/20], Step 5500, Train Loss: 0.3061, Val Avg Corr: 0.7763
Epoch [2/20], Step 6000, Train Loss: 0.4487, Val Avg Corr: 0.7834
Epoch [2/20], Step 6500, Train Loss: 0.3104, Val Avg Corr: 0.7868
Epoch [2/20], Step 7000, Train Loss: 0.3325, Val Avg Corr: 0.7896
  >>> New best validation model saved with Avg Corr: 0.7896 <<<
Epoch [2/20], Step 7500, Train Loss: 0.3288, Val Avg Corr: 0.7802
Epoch [2/20], Step 8000, Train Loss: 0.3042, Val Avg Corr: 0.7720
Epoch [2/20], Step 8500, Train Loss: 0.4720, Val Avg Corr: 0.7827
Epoch [2/20], Step 9000, Train Loss: 0.3500, Val Avg Corr: 0.7840
Epoch [2/20], Step 9500, Train Loss: 0.2984, Val Avg Corr: 0.7829
Epoch [2/20], Step 10000, Train Loss: 0.3978, Val Avg Corr: 0.7784
Epoch [2/20], Step 10500, Train Loss: 0.2337, Val Avg Corr: 0.7779
Epoch [2/20], Step 11000, Train Loss: 0.3459, Val Avg Corr: 0.7777
Epoch [2/20], Step 11500, Train Loss: 0.3164, Val Avg Corr: 0.7720
Epoch [2/20], Step 12000, Train Loss: 0.2876, Val Avg Corr: 0.7800
Epoch [2/20], Step 12500, Train Loss: 0.2931, Val Avg Corr: 0.7782
Epoch [2/20], Step 13000, Train Loss: 0.3788, Val Avg Corr: 0.7726
Epoch [2/20], Step 13500, Train Loss: 0.3839, Val Avg Corr: 0.7771
Epoch [2/20], Step 14000, Train Loss: 0.3506, Val Avg Corr: 0.7833
Epoch [2/20], Step 14500, Train Loss: 0.3809, Val Avg Corr: 0.7793
Epoch [2/20], Step 15000, Train Loss: 0.4030, Val Avg Corr: 0.7796
Epoch [2/20], Step 15500, Train Loss: 0.4477, Val Avg Corr: 0.7809
Epoch [2/20], Step 16000, Train Loss: 0.2858, Val Avg Corr: 0.7777
Epoch [2/20], Step 16500, Train Loss: 0.4152, Val Avg Corr: 0.7807
Epoch [2/20], Step 17000, Train Loss: 0.3692, Val Avg Corr: 0.7848
Epoch [2/20], Step 17500, Train Loss: 0.3074, Val Avg Corr: 0.7746
Epoch [2/20], Step 18000, Train Loss: 0.4409, Val Avg Corr: 0.7825
Epoch [2/20], Step 18500, Train Loss: 0.4507, Val Avg Corr: 0.7856
Epoch [2/20], Step 19000, Train Loss: 0.4240, Val Avg Corr: 0.7811
Epoch [2/20], Step 19500, Train Loss: 0.3322, Val Avg Corr: 0.7839
Epoch [2/20], Step 20000, Train Loss: 0.3896, Val Avg Corr: 0.7927
  >>> New best validation model saved with Avg Corr: 0.7927 <<<
Epoch [2/20], Step 20500, Train Loss: 0.2837, Val Avg Corr: 0.7925
Trial change detected: 722 -> 723, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.2601, Val Avg Corr: 0.7875
Epoch [2/20], Step 21500, Train Loss: 0.3728, Val Avg Corr: 0.7877
Epoch [2/20], Step 22000, Train Loss: 0.4513, Val Avg Corr: 0.7867
Epoch [2/20], Step 22500, Train Loss: 0.3924, Val Avg Corr: 0.7884
Epoch [2/20], Step 23000, Train Loss: 0.3461, Val Avg Corr: 0.7833
Epoch [2/20], Step 23500, Train Loss: 0.3371, Val Avg Corr: 0.7868
Epoch [2/20], Step 24000, Train Loss: 0.3265, Val Avg Corr: 0.7880
Epoch [2/20], Step 24500, Train Loss: 0.4514, Val Avg Corr: 0.7866
Epoch [2/20], Step 25000, Train Loss: 0.3172, Val Avg Corr: 0.7882
Epoch [2/20], Step 25500, Train Loss: 0.2762, Val Avg Corr: 0.7805
Epoch [2/20], Step 26000, Train Loss: 0.2790, Val Avg Corr: 0.7846
Epoch [2/20], Step 26500, Train Loss: 0.2602, Val Avg Corr: 0.7890
Epoch [2/20], Step 27000, Train Loss: 0.3912, Val Avg Corr: 0.7870
Epoch [2/20], Step 27500, Train Loss: 0.2442, Val Avg Corr: 0.7874
Epoch [2/20], Step 28000, Train Loss: 0.3719, Val Avg Corr: 0.7926
Epoch [2/20], Step 28500, Train Loss: 0.3466, Val Avg Corr: 0.7927
Epoch [2/20], Step 29000, Train Loss: 0.3190, Val Avg Corr: 0.7948
  >>> New best validation model saved with Avg Corr: 0.7948 <<<
Epoch [2/20], Step 29500, Train Loss: 0.2933, Val Avg Corr: 0.7969
  >>> New best validation model saved with Avg Corr: 0.7969 <<<
Epoch [2/20], Step 30000, Train Loss: 0.2931, Val Avg Corr: 0.7928
Epoch [2/20], Step 30500, Train Loss: 0.3480, Val Avg Corr: 0.8003
  >>> New best validation model saved with Avg Corr: 0.8003 <<<
Epoch [2/20], Step 31000, Train Loss: 0.3583, Val Avg Corr: 0.7996
Epoch [2/20], Step 31500, Train Loss: 0.3139, Val Avg Corr: 0.7936
Epoch [2/20], Step 32000, Train Loss: 0.4208, Val Avg Corr: 0.7887
Epoch [2/20], Step 32500, Train Loss: 0.3230, Val Avg Corr: 0.7988
Epoch [2/20], Step 33000, Train Loss: 0.2609, Val Avg Corr: 0.7945
Epoch [2/20], Step 33500, Train Loss: 0.2923, Val Avg Corr: 0.8019
  >>> New best validation model saved with Avg Corr: 0.8019 <<<
Epoch [2/20], Step 34000, Train Loss: 0.3421, Val Avg Corr: 0.7897
Epoch [2/20], Step 34500, Train Loss: 0.3110, Val Avg Corr: 0.7955
Epoch [2/20], Step 35000, Train Loss: 0.2566, Val Avg Corr: 0.7905
Epoch [2/20], Step 35500, Train Loss: 0.2755, Val Avg Corr: 0.7903
Epoch [2/20], Step 36000, Train Loss: 0.2844, Val Avg Corr: 0.7961
Epoch [2/20], Step 36500, Train Loss: 0.2788, Val Avg Corr: 0.7890
Epoch [2/20], Step 37000, Train Loss: 0.4775, Val Avg Corr: 0.7890
Epoch [2/20], Step 37500, Train Loss: 0.3866, Val Avg Corr: 0.7925
Epoch [2/20], Step 38000, Train Loss: 0.3084, Val Avg Corr: 0.7896
Epoch [2/20], Step 38500, Train Loss: 0.3445, Val Avg Corr: 0.7984
Epoch [2/20], Step 39000, Train Loss: 0.3552, Val Avg Corr: 0.7929
Epoch [2/20], Step 39500, Train Loss: 0.3427, Val Avg Corr: 0.7879
Epoch [2/20], Step 40000, Train Loss: 0.4470, Val Avg Corr: 0.7935
Epoch [2/20], Step 40500, Train Loss: 0.3462, Val Avg Corr: 0.7844
Epoch [2/20], Step 41000, Train Loss: 0.2303, Val Avg Corr: 0.7835
Trial change detected: 1433 -> 1434, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3028, Val Avg Corr: 0.7922
Epoch [2/20], Step 42000, Train Loss: 0.4093, Val Avg Corr: 0.7920
Epoch [2/20], Step 42500, Train Loss: 0.2363, Val Avg Corr: 0.7835
Epoch [2/20], Step 43000, Train Loss: 0.3429, Val Avg Corr: 0.7945
Epoch [2/20], Step 43500, Train Loss: 0.3757, Val Avg Corr: 0.8008
Epoch [2/20], Step 44000, Train Loss: 0.3596, Val Avg Corr: 0.7899
Epoch [2/20], Step 44500, Train Loss: 0.3421, Val Avg Corr: 0.7855
Epoch [2/20], Step 45000, Train Loss: 0.3863, Val Avg Corr: 0.7969
Epoch [2/20], Step 45500, Train Loss: 0.3138, Val Avg Corr: 0.7894
Epoch [2/20], Step 46000, Train Loss: 0.3423, Val Avg Corr: 0.7943
Epoch [2/20], Step 46500, Train Loss: 0.3704, Val Avg Corr: 0.8015
Epoch [2/20], Step 47000, Train Loss: 0.2712, Val Avg Corr: 0.7979
Epoch [2/20], Step 47500, Train Loss: 0.3034, Val Avg Corr: 0.7912
Epoch [2/20], Step 48000, Train Loss: 0.2935, Val Avg Corr: 0.7995
Epoch [2/20], Step 48500, Train Loss: 0.4040, Val Avg Corr: 0.7947
Epoch [2/20], Step 49000, Train Loss: 0.4050, Val Avg Corr: 0.8025
  >>> New best validation model saved with Avg Corr: 0.8025 <<<
Epoch [2/20], Step 49500, Train Loss: 0.3072, Val Avg Corr: 0.7967
Epoch [2/20], Step 50000, Train Loss: 0.3249, Val Avg Corr: 0.8014
Epoch [2/20], Step 50500, Train Loss: 0.3485, Val Avg Corr: 0.7987
Epoch [2/20], Step 51000, Train Loss: 0.3547, Val Avg Corr: 0.7961
Epoch [2/20], Step 51500, Train Loss: 0.3530, Val Avg Corr: 0.7968
Epoch [2/20], Step 52000, Train Loss: 0.3118, Val Avg Corr: 0.7957
Epoch [2/20], Step 52500, Train Loss: 0.3765, Val Avg Corr: 0.7989
Epoch [2/20], Step 53000, Train Loss: 0.3828, Val Avg Corr: 0.7972
Epoch [2/20], Step 53500, Train Loss: 0.4019, Val Avg Corr: 0.7975
Epoch [2/20], Step 54000, Train Loss: 0.3990, Val Avg Corr: 0.7941
Epoch [2/20], Step 54500, Train Loss: 0.4445, Val Avg Corr: 0.7977
Epoch [2/20], Step 55000, Train Loss: 0.3849, Val Avg Corr: 0.7945
Epoch [2/20], Step 55500, Train Loss: 0.3467, Val Avg Corr: 0.8045
  >>> New best validation model saved with Avg Corr: 0.8045 <<<
Epoch [2/20], Step 56000, Train Loss: 0.3577, Val Avg Corr: 0.8029
Epoch [2/20], Step 56500, Train Loss: 0.3875, Val Avg Corr: 0.8022
Epoch [2/20], Step 57000, Train Loss: 0.4150, Val Avg Corr: 0.8077
  >>> New best validation model saved with Avg Corr: 0.8077 <<<
Epoch [2/20], Step 57500, Train Loss: 0.3321, Val Avg Corr: 0.7969
Epoch [2/20], Step 58000, Train Loss: 0.2878, Val Avg Corr: 0.7877
Epoch [2/20], Step 58500, Train Loss: 0.3806, Val Avg Corr: 0.8028
Epoch [2/20], Step 59000, Train Loss: 0.3223, Val Avg Corr: 0.7981
Epoch [2/20], Step 59500, Train Loss: 0.3128, Val Avg Corr: 0.7992
Epoch [2/20], Step 60000, Train Loss: 0.2586, Val Avg Corr: 0.7990
Epoch [2/20], Step 60500, Train Loss: 0.3776, Val Avg Corr: 0.7902
Epoch [2/20], Step 61000, Train Loss: 0.3153, Val Avg Corr: 0.7977
Epoch [2/20], Step 61500, Train Loss: 0.3518, Val Avg Corr: 0.7974
Trial change detected: 2141 -> 2142, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.2813, Val Avg Corr: 0.8014
Epoch [2/20], Step 62500, Train Loss: 0.3578, Val Avg Corr: 0.7992
Epoch [2/20], Step 63000, Train Loss: 0.3281, Val Avg Corr: 0.8000
Epoch [2/20], Step 63500, Train Loss: 0.3966, Val Avg Corr: 0.7997
Epoch [2/20], Step 64000, Train Loss: 0.3429, Val Avg Corr: 0.7976
Epoch [2/20], Step 64500, Train Loss: 0.3088, Val Avg Corr: 0.7926
Epoch [2/20], Step 65000, Train Loss: 0.3056, Val Avg Corr: 0.8093
  >>> New best validation model saved with Avg Corr: 0.8093 <<<
Epoch [2/20], Step 65500, Train Loss: 0.3559, Val Avg Corr: 0.8064
Epoch [3/20], Step 500, Train Loss: 0.3468, Val Avg Corr: 0.8066
Epoch [3/20], Step 1000, Train Loss: 0.3697, Val Avg Corr: 0.8005
Epoch [3/20], Step 1500, Train Loss: 0.4280, Val Avg Corr: 0.8015
Epoch [3/20], Step 2000, Train Loss: 0.2988, Val Avg Corr: 0.7989
Epoch [3/20], Step 2500, Train Loss: 0.2478, Val Avg Corr: 0.8038
Epoch [3/20], Step 3000, Train Loss: 0.3989, Val Avg Corr: 0.8021
Epoch [3/20], Step 3500, Train Loss: 0.2941, Val Avg Corr: 0.8043
Epoch [3/20], Step 4000, Train Loss: 0.2809, Val Avg Corr: 0.8024
Epoch [3/20], Step 4500, Train Loss: 0.3992, Val Avg Corr: 0.8083
Epoch [3/20], Step 5000, Train Loss: 0.3703, Val Avg Corr: 0.8030
Epoch [3/20], Step 5500, Train Loss: 0.2614, Val Avg Corr: 0.7989
Epoch [3/20], Step 6000, Train Loss: 0.4084, Val Avg Corr: 0.8068
Epoch [3/20], Step 6500, Train Loss: 0.2759, Val Avg Corr: 0.8031
Epoch [3/20], Step 7000, Train Loss: 0.3063, Val Avg Corr: 0.8029
Epoch [3/20], Step 7500, Train Loss: 0.3050, Val Avg Corr: 0.8077
Epoch [3/20], Step 8000, Train Loss: 0.2613, Val Avg Corr: 0.7946
Epoch [3/20], Step 8500, Train Loss: 0.4401, Val Avg Corr: 0.8009
Epoch [3/20], Step 9000, Train Loss: 0.3071, Val Avg Corr: 0.8007
Epoch [3/20], Step 9500, Train Loss: 0.2630, Val Avg Corr: 0.8060
Epoch [3/20], Step 10000, Train Loss: 0.3627, Val Avg Corr: 0.7944
Epoch [3/20], Step 10500, Train Loss: 0.2162, Val Avg Corr: 0.7976
Epoch [3/20], Step 11000, Train Loss: 0.3047, Val Avg Corr: 0.7993
Epoch [3/20], Step 11500, Train Loss: 0.2853, Val Avg Corr: 0.7958
Epoch [3/20], Step 12000, Train Loss: 0.2822, Val Avg Corr: 0.7964
Epoch [3/20], Step 12500, Train Loss: 0.2805, Val Avg Corr: 0.7980
Epoch [3/20], Step 13000, Train Loss: 0.3287, Val Avg Corr: 0.7906
Epoch [3/20], Step 13500, Train Loss: 0.3486, Val Avg Corr: 0.7989
Epoch [3/20], Step 14000, Train Loss: 0.3183, Val Avg Corr: 0.7989
Epoch [3/20], Step 14500, Train Loss: 0.3399, Val Avg Corr: 0.7993
Epoch [3/20], Step 15000, Train Loss: 0.3677, Val Avg Corr: 0.7949
Epoch [3/20], Step 15500, Train Loss: 0.3917, Val Avg Corr: 0.8010
Epoch [3/20], Step 16000, Train Loss: 0.2725, Val Avg Corr: 0.8018
Epoch [3/20], Step 16500, Train Loss: 0.4087, Val Avg Corr: 0.8046
Epoch [3/20], Step 17000, Train Loss: 0.3190, Val Avg Corr: 0.8053
Epoch [3/20], Step 17500, Train Loss: 0.2787, Val Avg Corr: 0.7939
Epoch [3/20], Step 18000, Train Loss: 0.4071, Val Avg Corr: 0.7990
Epoch [3/20], Step 18500, Train Loss: 0.4007, Val Avg Corr: 0.8100
  >>> New best validation model saved with Avg Corr: 0.8100 <<<
Epoch [3/20], Step 19000, Train Loss: 0.3767, Val Avg Corr: 0.8010
Epoch [3/20], Step 19500, Train Loss: 0.2895, Val Avg Corr: 0.8065
Epoch [3/20], Step 20000, Train Loss: 0.3487, Val Avg Corr: 0.8124
  >>> New best validation model saved with Avg Corr: 0.8124 <<<
Epoch [3/20], Step 20500, Train Loss: 0.2565, Val Avg Corr: 0.8060
Trial change detected: 722 -> 723, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.2447, Val Avg Corr: 0.8027
Epoch [3/20], Step 21500, Train Loss: 0.3400, Val Avg Corr: 0.8069
Epoch [3/20], Step 22000, Train Loss: 0.4159, Val Avg Corr: 0.8048
Epoch [3/20], Step 22500, Train Loss: 0.3596, Val Avg Corr: 0.8081
Epoch [3/20], Step 23000, Train Loss: 0.3237, Val Avg Corr: 0.8037
Epoch [3/20], Step 23500, Train Loss: 0.3172, Val Avg Corr: 0.8050
Epoch [3/20], Step 24000, Train Loss: 0.2765, Val Avg Corr: 0.8092
Epoch [3/20], Step 24500, Train Loss: 0.4143, Val Avg Corr: 0.8091
Epoch [3/20], Step 25000, Train Loss: 0.2816, Val Avg Corr: 0.8039
Epoch [3/20], Step 25500, Train Loss: 0.2498, Val Avg Corr: 0.7964
Epoch [3/20], Step 26000, Train Loss: 0.2415, Val Avg Corr: 0.8094
Epoch [3/20], Step 26500, Train Loss: 0.2450, Val Avg Corr: 0.8102
Epoch [3/20], Step 27000, Train Loss: 0.3681, Val Avg Corr: 0.8122
Epoch [3/20], Step 27500, Train Loss: 0.2208, Val Avg Corr: 0.8100
Epoch [3/20], Step 28000, Train Loss: 0.3657, Val Avg Corr: 0.8112
Epoch [3/20], Step 28500, Train Loss: 0.3041, Val Avg Corr: 0.8019
Epoch [3/20], Step 29000, Train Loss: 0.2968, Val Avg Corr: 0.8085
Epoch [3/20], Step 29500, Train Loss: 0.2667, Val Avg Corr: 0.8124
  >>> New best validation model saved with Avg Corr: 0.8124 <<<
Epoch [3/20], Step 30000, Train Loss: 0.2564, Val Avg Corr: 0.8113
Epoch [3/20], Step 30500, Train Loss: 0.3145, Val Avg Corr: 0.8121
Epoch [3/20], Step 31000, Train Loss: 0.3325, Val Avg Corr: 0.8184
  >>> New best validation model saved with Avg Corr: 0.8184 <<<
Epoch [3/20], Step 31500, Train Loss: 0.2982, Val Avg Corr: 0.8143
Epoch [3/20], Step 32000, Train Loss: 0.3939, Val Avg Corr: 0.8090
Epoch [3/20], Step 32500, Train Loss: 0.2838, Val Avg Corr: 0.8171
Epoch [3/20], Step 33000, Train Loss: 0.2405, Val Avg Corr: 0.8190
  >>> New best validation model saved with Avg Corr: 0.8190 <<<
Epoch [3/20], Step 33500, Train Loss: 0.2649, Val Avg Corr: 0.8241
  >>> New best validation model saved with Avg Corr: 0.8241 <<<
Epoch [3/20], Step 34000, Train Loss: 0.3213, Val Avg Corr: 0.8100
Epoch [3/20], Step 34500, Train Loss: 0.2525, Val Avg Corr: 0.8118
Epoch [3/20], Step 35000, Train Loss: 0.2551, Val Avg Corr: 0.8188
Epoch [3/20], Step 35500, Train Loss: 0.2414, Val Avg Corr: 0.8135
Epoch [3/20], Step 36000, Train Loss: 0.2510, Val Avg Corr: 0.8135
Epoch [3/20], Step 36500, Train Loss: 0.2590, Val Avg Corr: 0.8135
Epoch [3/20], Step 37000, Train Loss: 0.4388, Val Avg Corr: 0.8130
Epoch [3/20], Step 37500, Train Loss: 0.3721, Val Avg Corr: 0.8089
Epoch [3/20], Step 38000, Train Loss: 0.2706, Val Avg Corr: 0.8131
Epoch [3/20], Step 38500, Train Loss: 0.3318, Val Avg Corr: 0.8140
Epoch [3/20], Step 39000, Train Loss: 0.3429, Val Avg Corr: 0.8172
Epoch [3/20], Step 39500, Train Loss: 0.3514, Val Avg Corr: 0.8136
Epoch [3/20], Step 40000, Train Loss: 0.3896, Val Avg Corr: 0.8124
Epoch [3/20], Step 40500, Train Loss: 0.3219, Val Avg Corr: 0.8086
Epoch [3/20], Step 41000, Train Loss: 0.2190, Val Avg Corr: 0.8077
Trial change detected: 1433 -> 1434, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.2623, Val Avg Corr: 0.8130
Epoch [3/20], Step 42000, Train Loss: 0.3662, Val Avg Corr: 0.8112
Epoch [3/20], Step 42500, Train Loss: 0.2206, Val Avg Corr: 0.8071
Epoch [3/20], Step 43000, Train Loss: 0.3209, Val Avg Corr: 0.8127
Epoch [3/20], Step 43500, Train Loss: 0.3603, Val Avg Corr: 0.8112
Epoch [3/20], Step 44000, Train Loss: 0.3381, Val Avg Corr: 0.7975
Epoch [3/20], Step 44500, Train Loss: 0.3101, Val Avg Corr: 0.8094
Epoch [3/20], Step 45000, Train Loss: 0.3567, Val Avg Corr: 0.8136
Epoch [3/20], Step 45500, Train Loss: 0.3103, Val Avg Corr: 0.8062
Epoch [3/20], Step 46000, Train Loss: 0.3341, Val Avg Corr: 0.8150
Epoch [3/20], Step 46500, Train Loss: 0.3346, Val Avg Corr: 0.8146
Epoch [3/20], Step 47000, Train Loss: 0.2343, Val Avg Corr: 0.8189
Epoch [3/20], Step 47500, Train Loss: 0.2928, Val Avg Corr: 0.8205
Epoch [3/20], Step 48000, Train Loss: 0.2700, Val Avg Corr: 0.8174
Epoch [3/20], Step 48500, Train Loss: 0.3771, Val Avg Corr: 0.8169
Epoch [3/20], Step 49000, Train Loss: 0.3822, Val Avg Corr: 0.8135
Epoch [3/20], Step 49500, Train Loss: 0.2719, Val Avg Corr: 0.8080
Epoch [3/20], Step 50000, Train Loss: 0.3198, Val Avg Corr: 0.8199
Epoch [3/20], Step 50500, Train Loss: 0.3223, Val Avg Corr: 0.8212
Epoch [3/20], Step 51000, Train Loss: 0.3558, Val Avg Corr: 0.8095
Epoch [3/20], Step 51500, Train Loss: 0.3205, Val Avg Corr: 0.8098
Epoch [3/20], Step 52000, Train Loss: 0.2878, Val Avg Corr: 0.8135
Epoch [3/20], Step 52500, Train Loss: 0.3518, Val Avg Corr: 0.8143
Epoch [3/20], Step 53000, Train Loss: 0.3467, Val Avg Corr: 0.8150
Epoch [3/20], Step 53500, Train Loss: 0.3612, Val Avg Corr: 0.8168
Epoch [3/20], Step 54000, Train Loss: 0.3759, Val Avg Corr: 0.8157
Epoch [3/20], Step 54500, Train Loss: 0.4064, Val Avg Corr: 0.8110
Epoch [3/20], Step 55000, Train Loss: 0.3582, Val Avg Corr: 0.8168
Epoch [3/20], Step 55500, Train Loss: 0.3172, Val Avg Corr: 0.8112
Epoch [3/20], Step 56000, Train Loss: 0.3270, Val Avg Corr: 0.8157
Epoch [3/20], Step 56500, Train Loss: 0.3723, Val Avg Corr: 0.8170
Epoch [3/20], Step 57000, Train Loss: 0.3881, Val Avg Corr: 0.8166
Epoch [3/20], Step 57500, Train Loss: 0.3189, Val Avg Corr: 0.8151
Epoch [3/20], Step 58000, Train Loss: 0.2780, Val Avg Corr: 0.8103
Epoch [3/20], Step 58500, Train Loss: 0.3427, Val Avg Corr: 0.8215
Early stopping triggered after 58500 steps in epoch 3.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8241
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8266, Y=0.7994, Avg=0.8130

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 9) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    2.0    1.0    0.0    0.0    0.0    0.0    1.0    1.0    0.0    0.0
Row 1:    2.0    1.0    0.0    0.0    0.0    0.0    0.0    1.0    0.0    0.0
Row 2:    1.0    1.0    0.0    0.0    0.0    0.0    0.0    1.0    0.0    0.0
Row 3:    1.0    1.0    0.0    0.0    0.0    0.0    0.0    1.0    0.0    0.0
Row 4:    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.1056, Val Avg Corr: 0.0230
  >>> New best validation model saved with Avg Corr: 0.0230 <<<
Epoch [1/20], Step 1000, Train Loss: 1.2307, Val Avg Corr: 0.0601
  >>> New best validation model saved with Avg Corr: 0.0601 <<<
Epoch [1/20], Step 1500, Train Loss: 1.2268, Val Avg Corr: 0.0577
Epoch [1/20], Step 2000, Train Loss: 0.9767, Val Avg Corr: 0.1330
  >>> New best validation model saved with Avg Corr: 0.1330 <<<
Epoch [1/20], Step 2500, Train Loss: 0.8392, Val Avg Corr: 0.1954
  >>> New best validation model saved with Avg Corr: 0.1954 <<<
Epoch [1/20], Step 3000, Train Loss: 0.9000, Val Avg Corr: 0.1932
Epoch [1/20], Step 3500, Train Loss: 1.0631, Val Avg Corr: 0.2203
  >>> New best validation model saved with Avg Corr: 0.2203 <<<
Epoch [1/20], Step 4000, Train Loss: 0.8585, Val Avg Corr: 0.2489
  >>> New best validation model saved with Avg Corr: 0.2489 <<<
Epoch [1/20], Step 4500, Train Loss: 0.8426, Val Avg Corr: 0.1926
Epoch [1/20], Step 5000, Train Loss: 1.0124, Val Avg Corr: 0.2457
Epoch [1/20], Step 5500, Train Loss: 0.7871, Val Avg Corr: 0.3686
  >>> New best validation model saved with Avg Corr: 0.3686 <<<
Epoch [1/20], Step 6000, Train Loss: 0.9916, Val Avg Corr: 0.3469
Epoch [1/20], Step 6500, Train Loss: 0.7025, Val Avg Corr: 0.3691
  >>> New best validation model saved with Avg Corr: 0.3691 <<<
Epoch [1/20], Step 7000, Train Loss: 0.9059, Val Avg Corr: 0.3858
  >>> New best validation model saved with Avg Corr: 0.3858 <<<
Epoch [1/20], Step 7500, Train Loss: 0.8041, Val Avg Corr: 0.4278
  >>> New best validation model saved with Avg Corr: 0.4278 <<<
Epoch [1/20], Step 8000, Train Loss: 0.8313, Val Avg Corr: 0.4441
  >>> New best validation model saved with Avg Corr: 0.4441 <<<
Epoch [1/20], Step 8500, Train Loss: 0.8406, Val Avg Corr: 0.4664
  >>> New best validation model saved with Avg Corr: 0.4664 <<<
Epoch [1/20], Step 9000, Train Loss: 0.7057, Val Avg Corr: 0.4566
Epoch [1/20], Step 9500, Train Loss: 0.8412, Val Avg Corr: 0.4547
Epoch [1/20], Step 10000, Train Loss: 0.6981, Val Avg Corr: 0.4650
Epoch [1/20], Step 10500, Train Loss: 0.5642, Val Avg Corr: 0.4098
Epoch [1/20], Step 11000, Train Loss: 0.7003, Val Avg Corr: 0.4236
Epoch [1/20], Step 11500, Train Loss: 0.8515, Val Avg Corr: 0.4914
  >>> New best validation model saved with Avg Corr: 0.4914 <<<
Epoch [1/20], Step 12000, Train Loss: 0.5989, Val Avg Corr: 0.4603
Epoch [1/20], Step 12500, Train Loss: 0.9213, Val Avg Corr: 0.5005
  >>> New best validation model saved with Avg Corr: 0.5005 <<<
Epoch [1/20], Step 13000, Train Loss: 0.7437, Val Avg Corr: 0.5426
  >>> New best validation model saved with Avg Corr: 0.5426 <<<
Epoch [1/20], Step 13500, Train Loss: 0.7418, Val Avg Corr: 0.5424
Epoch [1/20], Step 14000, Train Loss: 0.6899, Val Avg Corr: 0.5412
Epoch [1/20], Step 14500, Train Loss: 0.5712, Val Avg Corr: 0.5360
Epoch [1/20], Step 15000, Train Loss: 0.7369, Val Avg Corr: 0.5819
  >>> New best validation model saved with Avg Corr: 0.5819 <<<
Epoch [1/20], Step 15500, Train Loss: 0.8056, Val Avg Corr: 0.5688
Epoch [1/20], Step 16000, Train Loss: 0.5454, Val Avg Corr: 0.5832
  >>> New best validation model saved with Avg Corr: 0.5832 <<<
Epoch [1/20], Step 16500, Train Loss: 0.7198, Val Avg Corr: 0.5792
Epoch [1/20], Step 17000, Train Loss: 0.8839, Val Avg Corr: 0.5881
  >>> New best validation model saved with Avg Corr: 0.5881 <<<
Epoch [1/20], Step 17500, Train Loss: 0.5796, Val Avg Corr: 0.5803
Epoch [1/20], Step 18000, Train Loss: 0.6321, Val Avg Corr: 0.5885
  >>> New best validation model saved with Avg Corr: 0.5885 <<<
Epoch [1/20], Step 18500, Train Loss: 0.6904, Val Avg Corr: 0.6113
  >>> New best validation model saved with Avg Corr: 0.6113 <<<
Epoch [1/20], Step 19000, Train Loss: 0.5383, Val Avg Corr: 0.6100
Epoch [1/20], Step 19500, Train Loss: 0.6817, Val Avg Corr: 0.6142
  >>> New best validation model saved with Avg Corr: 0.6142 <<<
Epoch [1/20], Step 20000, Train Loss: 0.4988, Val Avg Corr: 0.6164
  >>> New best validation model saved with Avg Corr: 0.6164 <<<
Epoch [1/20], Step 20500, Train Loss: 0.5302, Val Avg Corr: 0.6307
  >>> New best validation model saved with Avg Corr: 0.6307 <<<
Trial change detected: 715 -> 716, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.4945, Val Avg Corr: 0.6358
  >>> New best validation model saved with Avg Corr: 0.6358 <<<
Epoch [1/20], Step 21500, Train Loss: 0.5353, Val Avg Corr: 0.6374
  >>> New best validation model saved with Avg Corr: 0.6374 <<<
Epoch [1/20], Step 22000, Train Loss: 0.5660, Val Avg Corr: 0.6353
Epoch [1/20], Step 22500, Train Loss: 0.6244, Val Avg Corr: 0.6324
Epoch [1/20], Step 23000, Train Loss: 0.7420, Val Avg Corr: 0.6469
  >>> New best validation model saved with Avg Corr: 0.6469 <<<
Epoch [1/20], Step 23500, Train Loss: 0.5524, Val Avg Corr: 0.6485
  >>> New best validation model saved with Avg Corr: 0.6485 <<<
Epoch [1/20], Step 24000, Train Loss: 0.5371, Val Avg Corr: 0.6576
  >>> New best validation model saved with Avg Corr: 0.6576 <<<
Epoch [1/20], Step 24500, Train Loss: 0.6293, Val Avg Corr: 0.6690
  >>> New best validation model saved with Avg Corr: 0.6690 <<<
Epoch [1/20], Step 25000, Train Loss: 0.6292, Val Avg Corr: 0.6601
Epoch [1/20], Step 25500, Train Loss: 0.5695, Val Avg Corr: 0.6752
  >>> New best validation model saved with Avg Corr: 0.6752 <<<
Epoch [1/20], Step 26000, Train Loss: 0.6224, Val Avg Corr: 0.6756
  >>> New best validation model saved with Avg Corr: 0.6756 <<<
Epoch [1/20], Step 26500, Train Loss: 0.3766, Val Avg Corr: 0.6769
  >>> New best validation model saved with Avg Corr: 0.6769 <<<
Epoch [1/20], Step 27000, Train Loss: 0.3995, Val Avg Corr: 0.6774
  >>> New best validation model saved with Avg Corr: 0.6774 <<<
Epoch [1/20], Step 27500, Train Loss: 0.4688, Val Avg Corr: 0.6795
  >>> New best validation model saved with Avg Corr: 0.6795 <<<
Epoch [1/20], Step 28000, Train Loss: 0.5218, Val Avg Corr: 0.6795
Epoch [1/20], Step 28500, Train Loss: 0.5824, Val Avg Corr: 0.6777
Epoch [1/20], Step 29000, Train Loss: 0.5446, Val Avg Corr: 0.6953
  >>> New best validation model saved with Avg Corr: 0.6953 <<<
Epoch [1/20], Step 29500, Train Loss: 0.4738, Val Avg Corr: 0.6962
  >>> New best validation model saved with Avg Corr: 0.6962 <<<
Epoch [1/20], Step 30000, Train Loss: 0.4089, Val Avg Corr: 0.7007
  >>> New best validation model saved with Avg Corr: 0.7007 <<<
Epoch [1/20], Step 30500, Train Loss: 0.5327, Val Avg Corr: 0.7088
  >>> New best validation model saved with Avg Corr: 0.7088 <<<
Epoch [1/20], Step 31000, Train Loss: 0.5213, Val Avg Corr: 0.6974
Epoch [1/20], Step 31500, Train Loss: 0.4839, Val Avg Corr: 0.7060
Epoch [1/20], Step 32000, Train Loss: 0.4020, Val Avg Corr: 0.7030
Epoch [1/20], Step 32500, Train Loss: 0.5090, Val Avg Corr: 0.6985
Epoch [1/20], Step 33000, Train Loss: 0.3362, Val Avg Corr: 0.7123
  >>> New best validation model saved with Avg Corr: 0.7123 <<<
Epoch [1/20], Step 33500, Train Loss: 0.4671, Val Avg Corr: 0.7064
Epoch [1/20], Step 34000, Train Loss: 0.4940, Val Avg Corr: 0.6980
Epoch [1/20], Step 34500, Train Loss: 0.4881, Val Avg Corr: 0.7093
Epoch [1/20], Step 35000, Train Loss: 0.4021, Val Avg Corr: 0.7090
Epoch [1/20], Step 35500, Train Loss: 0.4058, Val Avg Corr: 0.7125
  >>> New best validation model saved with Avg Corr: 0.7125 <<<
Epoch [1/20], Step 36000, Train Loss: 0.3901, Val Avg Corr: 0.7146
  >>> New best validation model saved with Avg Corr: 0.7146 <<<
Epoch [1/20], Step 36500, Train Loss: 0.4567, Val Avg Corr: 0.7191
  >>> New best validation model saved with Avg Corr: 0.7191 <<<
Epoch [1/20], Step 37000, Train Loss: 0.4133, Val Avg Corr: 0.7166
Epoch [1/20], Step 37500, Train Loss: 0.5586, Val Avg Corr: 0.7301
  >>> New best validation model saved with Avg Corr: 0.7301 <<<
Epoch [1/20], Step 38000, Train Loss: 0.4961, Val Avg Corr: 0.7229
Epoch [1/20], Step 38500, Train Loss: 0.5141, Val Avg Corr: 0.7220
Epoch [1/20], Step 39000, Train Loss: 0.3726, Val Avg Corr: 0.7220
Epoch [1/20], Step 39500, Train Loss: 0.3719, Val Avg Corr: 0.7259
Epoch [1/20], Step 40000, Train Loss: 0.4653, Val Avg Corr: 0.7225
Epoch [1/20], Step 40500, Train Loss: 0.4074, Val Avg Corr: 0.7155
Epoch [1/20], Step 41000, Train Loss: 0.3465, Val Avg Corr: 0.7255
Trial change detected: 1438 -> 1439, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.4391, Val Avg Corr: 0.7321
  >>> New best validation model saved with Avg Corr: 0.7321 <<<
Epoch [1/20], Step 42000, Train Loss: 0.4144, Val Avg Corr: 0.7349
  >>> New best validation model saved with Avg Corr: 0.7349 <<<
Epoch [1/20], Step 42500, Train Loss: 0.4326, Val Avg Corr: 0.7288
Epoch [1/20], Step 43000, Train Loss: 0.4228, Val Avg Corr: 0.7392
  >>> New best validation model saved with Avg Corr: 0.7392 <<<
Epoch [1/20], Step 43500, Train Loss: 0.3754, Val Avg Corr: 0.7416
  >>> New best validation model saved with Avg Corr: 0.7416 <<<
Epoch [1/20], Step 44000, Train Loss: 0.4184, Val Avg Corr: 0.7334
Epoch [1/20], Step 44500, Train Loss: 0.4013, Val Avg Corr: 0.7418
  >>> New best validation model saved with Avg Corr: 0.7418 <<<
Epoch [1/20], Step 45000, Train Loss: 0.3844, Val Avg Corr: 0.7310
Epoch [1/20], Step 45500, Train Loss: 0.4903, Val Avg Corr: 0.7457
  >>> New best validation model saved with Avg Corr: 0.7457 <<<
Epoch [1/20], Step 46000, Train Loss: 0.4524, Val Avg Corr: 0.7468
  >>> New best validation model saved with Avg Corr: 0.7468 <<<
Epoch [1/20], Step 46500, Train Loss: 0.3161, Val Avg Corr: 0.7415
Epoch [1/20], Step 47000, Train Loss: 0.3352, Val Avg Corr: 0.7430
Epoch [1/20], Step 47500, Train Loss: 0.4292, Val Avg Corr: 0.7444
Epoch [1/20], Step 48000, Train Loss: 0.3851, Val Avg Corr: 0.7471
  >>> New best validation model saved with Avg Corr: 0.7471 <<<
Epoch [1/20], Step 48500, Train Loss: 0.5004, Val Avg Corr: 0.7511
  >>> New best validation model saved with Avg Corr: 0.7511 <<<
Epoch [1/20], Step 49000, Train Loss: 0.4527, Val Avg Corr: 0.7475
Epoch [1/20], Step 49500, Train Loss: 0.3696, Val Avg Corr: 0.7359
Epoch [1/20], Step 50000, Train Loss: 0.3664, Val Avg Corr: 0.7435
Epoch [1/20], Step 50500, Train Loss: 0.4321, Val Avg Corr: 0.7466
Epoch [1/20], Step 51000, Train Loss: 0.3608, Val Avg Corr: 0.7346
Epoch [1/20], Step 51500, Train Loss: 0.3794, Val Avg Corr: 0.7505
Epoch [1/20], Step 52000, Train Loss: 0.4053, Val Avg Corr: 0.7485
Epoch [1/20], Step 52500, Train Loss: 0.3743, Val Avg Corr: 0.7513
  >>> New best validation model saved with Avg Corr: 0.7513 <<<
Epoch [1/20], Step 53000, Train Loss: 0.4891, Val Avg Corr: 0.7511
Epoch [1/20], Step 53500, Train Loss: 0.4541, Val Avg Corr: 0.7645
  >>> New best validation model saved with Avg Corr: 0.7645 <<<
Epoch [1/20], Step 54000, Train Loss: 0.4422, Val Avg Corr: 0.7484
Epoch [1/20], Step 54500, Train Loss: 0.5516, Val Avg Corr: 0.7438
Epoch [1/20], Step 55000, Train Loss: 0.3975, Val Avg Corr: 0.7577
Epoch [1/20], Step 55500, Train Loss: 0.4311, Val Avg Corr: 0.7468
Epoch [1/20], Step 56000, Train Loss: 0.4121, Val Avg Corr: 0.7498
Epoch [1/20], Step 56500, Train Loss: 0.5493, Val Avg Corr: 0.7541
Epoch [1/20], Step 57000, Train Loss: 0.4592, Val Avg Corr: 0.7526
Epoch [1/20], Step 57500, Train Loss: 0.4449, Val Avg Corr: 0.7581
Epoch [1/20], Step 58000, Train Loss: 0.3790, Val Avg Corr: 0.7551
Epoch [1/20], Step 58500, Train Loss: 0.3618, Val Avg Corr: 0.7554
Epoch [1/20], Step 59000, Train Loss: 0.3854, Val Avg Corr: 0.7591
Epoch [1/20], Step 59500, Train Loss: 0.3828, Val Avg Corr: 0.7595
Epoch [1/20], Step 60000, Train Loss: 0.3727, Val Avg Corr: 0.7526
Epoch [1/20], Step 60500, Train Loss: 0.4416, Val Avg Corr: 0.7660
  >>> New best validation model saved with Avg Corr: 0.7660 <<<
Epoch [1/20], Step 61000, Train Loss: 0.3208, Val Avg Corr: 0.7624
Epoch [1/20], Step 61500, Train Loss: 0.4435, Val Avg Corr: 0.7535
Trial change detected: 2145 -> 2146, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.3874, Val Avg Corr: 0.7582
Epoch [1/20], Step 62500, Train Loss: 0.4107, Val Avg Corr: 0.7640
Epoch [1/20], Step 63000, Train Loss: 0.3127, Val Avg Corr: 0.7615
Epoch [1/20], Step 63500, Train Loss: 0.3952, Val Avg Corr: 0.7719
  >>> New best validation model saved with Avg Corr: 0.7719 <<<
Epoch [1/20], Step 64000, Train Loss: 0.4141, Val Avg Corr: 0.7741
  >>> New best validation model saved with Avg Corr: 0.7741 <<<
Epoch [1/20], Step 64500, Train Loss: 0.4844, Val Avg Corr: 0.7658
Epoch [1/20], Step 65000, Train Loss: 0.3479, Val Avg Corr: 0.7594
Epoch [1/20], Step 65500, Train Loss: 0.4110, Val Avg Corr: 0.7697
Epoch [2/20], Step 500, Train Loss: 0.3654, Val Avg Corr: 0.7685
Epoch [2/20], Step 1000, Train Loss: 0.4934, Val Avg Corr: 0.7689
Epoch [2/20], Step 1500, Train Loss: 0.5054, Val Avg Corr: 0.7658
Epoch [2/20], Step 2000, Train Loss: 0.3816, Val Avg Corr: 0.7729
Epoch [2/20], Step 2500, Train Loss: 0.3066, Val Avg Corr: 0.7754
  >>> New best validation model saved with Avg Corr: 0.7754 <<<
Epoch [2/20], Step 3000, Train Loss: 0.3302, Val Avg Corr: 0.7731
Epoch [2/20], Step 3500, Train Loss: 0.4186, Val Avg Corr: 0.7639
Epoch [2/20], Step 4000, Train Loss: 0.3139, Val Avg Corr: 0.7781
  >>> New best validation model saved with Avg Corr: 0.7781 <<<
Epoch [2/20], Step 4500, Train Loss: 0.3965, Val Avg Corr: 0.7789
  >>> New best validation model saved with Avg Corr: 0.7789 <<<
Epoch [2/20], Step 5000, Train Loss: 0.5183, Val Avg Corr: 0.7739
Epoch [2/20], Step 5500, Train Loss: 0.3375, Val Avg Corr: 0.7677
Epoch [2/20], Step 6000, Train Loss: 0.3570, Val Avg Corr: 0.7715
Epoch [2/20], Step 6500, Train Loss: 0.2744, Val Avg Corr: 0.7690
Epoch [2/20], Step 7000, Train Loss: 0.3938, Val Avg Corr: 0.7806
  >>> New best validation model saved with Avg Corr: 0.7806 <<<
Epoch [2/20], Step 7500, Train Loss: 0.3651, Val Avg Corr: 0.7690
Epoch [2/20], Step 8000, Train Loss: 0.3841, Val Avg Corr: 0.7705
Epoch [2/20], Step 8500, Train Loss: 0.4841, Val Avg Corr: 0.7672
Epoch [2/20], Step 9000, Train Loss: 0.3697, Val Avg Corr: 0.7793
Epoch [2/20], Step 9500, Train Loss: 0.3908, Val Avg Corr: 0.7672
Epoch [2/20], Step 10000, Train Loss: 0.2913, Val Avg Corr: 0.7705
Epoch [2/20], Step 10500, Train Loss: 0.2751, Val Avg Corr: 0.7597
Epoch [2/20], Step 11000, Train Loss: 0.3103, Val Avg Corr: 0.7669
Epoch [2/20], Step 11500, Train Loss: 0.3577, Val Avg Corr: 0.7705
Epoch [2/20], Step 12000, Train Loss: 0.3571, Val Avg Corr: 0.7650
Epoch [2/20], Step 12500, Train Loss: 0.4082, Val Avg Corr: 0.7665
Epoch [2/20], Step 13000, Train Loss: 0.3341, Val Avg Corr: 0.7709
Epoch [2/20], Step 13500, Train Loss: 0.4031, Val Avg Corr: 0.7783
Epoch [2/20], Step 14000, Train Loss: 0.3949, Val Avg Corr: 0.7729
Epoch [2/20], Step 14500, Train Loss: 0.2967, Val Avg Corr: 0.7715
Epoch [2/20], Step 15000, Train Loss: 0.3661, Val Avg Corr: 0.7775
Epoch [2/20], Step 15500, Train Loss: 0.5142, Val Avg Corr: 0.7727
Epoch [2/20], Step 16000, Train Loss: 0.3075, Val Avg Corr: 0.7739
Epoch [2/20], Step 16500, Train Loss: 0.4410, Val Avg Corr: 0.7759
Epoch [2/20], Step 17000, Train Loss: 0.4657, Val Avg Corr: 0.7771
Epoch [2/20], Step 17500, Train Loss: 0.3878, Val Avg Corr: 0.7707
Epoch [2/20], Step 18000, Train Loss: 0.4118, Val Avg Corr: 0.7713
Epoch [2/20], Step 18500, Train Loss: 0.4315, Val Avg Corr: 0.7769
Epoch [2/20], Step 19000, Train Loss: 0.3063, Val Avg Corr: 0.7772
Epoch [2/20], Step 19500, Train Loss: 0.4273, Val Avg Corr: 0.7737
Epoch [2/20], Step 20000, Train Loss: 0.3466, Val Avg Corr: 0.7762
Epoch [2/20], Step 20500, Train Loss: 0.3640, Val Avg Corr: 0.7772
Trial change detected: 715 -> 716, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.3044, Val Avg Corr: 0.7812
  >>> New best validation model saved with Avg Corr: 0.7812 <<<
Epoch [2/20], Step 21500, Train Loss: 0.3637, Val Avg Corr: 0.7746
Epoch [2/20], Step 22000, Train Loss: 0.4257, Val Avg Corr: 0.7758
Epoch [2/20], Step 22500, Train Loss: 0.4436, Val Avg Corr: 0.7730
Epoch [2/20], Step 23000, Train Loss: 0.5415, Val Avg Corr: 0.7793
Epoch [2/20], Step 23500, Train Loss: 0.3239, Val Avg Corr: 0.7743
Epoch [2/20], Step 24000, Train Loss: 0.3585, Val Avg Corr: 0.7822
  >>> New best validation model saved with Avg Corr: 0.7822 <<<
Epoch [2/20], Step 24500, Train Loss: 0.4468, Val Avg Corr: 0.7862
  >>> New best validation model saved with Avg Corr: 0.7862 <<<
Epoch [2/20], Step 25000, Train Loss: 0.4391, Val Avg Corr: 0.7796
Epoch [2/20], Step 25500, Train Loss: 0.3709, Val Avg Corr: 0.7937
  >>> New best validation model saved with Avg Corr: 0.7937 <<<
Epoch [2/20], Step 26000, Train Loss: 0.4049, Val Avg Corr: 0.7882
Epoch [2/20], Step 26500, Train Loss: 0.2390, Val Avg Corr: 0.7828
Epoch [2/20], Step 27000, Train Loss: 0.2804, Val Avg Corr: 0.7837
Epoch [2/20], Step 27500, Train Loss: 0.3928, Val Avg Corr: 0.7773
Epoch [2/20], Step 28000, Train Loss: 0.3808, Val Avg Corr: 0.7801
Epoch [2/20], Step 28500, Train Loss: 0.4208, Val Avg Corr: 0.7728
Epoch [2/20], Step 29000, Train Loss: 0.3916, Val Avg Corr: 0.7840
Epoch [2/20], Step 29500, Train Loss: 0.3521, Val Avg Corr: 0.7831
Epoch [2/20], Step 30000, Train Loss: 0.3013, Val Avg Corr: 0.7825
Epoch [2/20], Step 30500, Train Loss: 0.3625, Val Avg Corr: 0.7840
Epoch [2/20], Step 31000, Train Loss: 0.4255, Val Avg Corr: 0.7840
Epoch [2/20], Step 31500, Train Loss: 0.3864, Val Avg Corr: 0.7938
  >>> New best validation model saved with Avg Corr: 0.7938 <<<
Epoch [2/20], Step 32000, Train Loss: 0.3342, Val Avg Corr: 0.7930
Epoch [2/20], Step 32500, Train Loss: 0.3744, Val Avg Corr: 0.7855
Epoch [2/20], Step 33000, Train Loss: 0.2523, Val Avg Corr: 0.7855
Epoch [2/20], Step 33500, Train Loss: 0.3636, Val Avg Corr: 0.7775
Epoch [2/20], Step 34000, Train Loss: 0.3723, Val Avg Corr: 0.7753
Epoch [2/20], Step 34500, Train Loss: 0.3885, Val Avg Corr: 0.7846
Epoch [2/20], Step 35000, Train Loss: 0.2783, Val Avg Corr: 0.7840
Epoch [2/20], Step 35500, Train Loss: 0.2855, Val Avg Corr: 0.7827
Epoch [2/20], Step 36000, Train Loss: 0.2833, Val Avg Corr: 0.7785
Epoch [2/20], Step 36500, Train Loss: 0.2935, Val Avg Corr: 0.7800
Epoch [2/20], Step 37000, Train Loss: 0.3529, Val Avg Corr: 0.7812
Epoch [2/20], Step 37500, Train Loss: 0.4536, Val Avg Corr: 0.7822
Epoch [2/20], Step 38000, Train Loss: 0.3812, Val Avg Corr: 0.7879
Epoch [2/20], Step 38500, Train Loss: 0.4140, Val Avg Corr: 0.7822
Epoch [2/20], Step 39000, Train Loss: 0.2927, Val Avg Corr: 0.7859
Epoch [2/20], Step 39500, Train Loss: 0.3001, Val Avg Corr: 0.7903
Epoch [2/20], Step 40000, Train Loss: 0.3858, Val Avg Corr: 0.7804
Epoch [2/20], Step 40500, Train Loss: 0.3090, Val Avg Corr: 0.7769
Epoch [2/20], Step 41000, Train Loss: 0.2580, Val Avg Corr: 0.7817
Trial change detected: 1438 -> 1439, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3742, Val Avg Corr: 0.7931
Epoch [2/20], Step 42000, Train Loss: 0.3161, Val Avg Corr: 0.7972
  >>> New best validation model saved with Avg Corr: 0.7972 <<<
Epoch [2/20], Step 42500, Train Loss: 0.3374, Val Avg Corr: 0.7919
Epoch [2/20], Step 43000, Train Loss: 0.3162, Val Avg Corr: 0.8003
  >>> New best validation model saved with Avg Corr: 0.8003 <<<
Epoch [2/20], Step 43500, Train Loss: 0.3200, Val Avg Corr: 0.7920
Epoch [2/20], Step 44000, Train Loss: 0.3465, Val Avg Corr: 0.7858
Epoch [2/20], Step 44500, Train Loss: 0.3439, Val Avg Corr: 0.7924
Epoch [2/20], Step 45000, Train Loss: 0.3619, Val Avg Corr: 0.7836
Epoch [2/20], Step 45500, Train Loss: 0.3804, Val Avg Corr: 0.7870
Epoch [2/20], Step 46000, Train Loss: 0.3477, Val Avg Corr: 0.7919
Epoch [2/20], Step 46500, Train Loss: 0.2937, Val Avg Corr: 0.7900
Epoch [2/20], Step 47000, Train Loss: 0.2525, Val Avg Corr: 0.7873
Epoch [2/20], Step 47500, Train Loss: 0.3730, Val Avg Corr: 0.7972
Epoch [2/20], Step 48000, Train Loss: 0.3321, Val Avg Corr: 0.7901
Epoch [2/20], Step 48500, Train Loss: 0.4238, Val Avg Corr: 0.7893
Epoch [2/20], Step 49000, Train Loss: 0.3716, Val Avg Corr: 0.7925
Epoch [2/20], Step 49500, Train Loss: 0.2761, Val Avg Corr: 0.7759
Epoch [2/20], Step 50000, Train Loss: 0.3215, Val Avg Corr: 0.7845
Epoch [2/20], Step 50500, Train Loss: 0.4195, Val Avg Corr: 0.7926
Epoch [2/20], Step 51000, Train Loss: 0.3198, Val Avg Corr: 0.7857
Epoch [2/20], Step 51500, Train Loss: 0.2836, Val Avg Corr: 0.7886
Epoch [2/20], Step 52000, Train Loss: 0.3281, Val Avg Corr: 0.7846
Epoch [2/20], Step 52500, Train Loss: 0.3520, Val Avg Corr: 0.7969
Epoch [2/20], Step 53000, Train Loss: 0.3710, Val Avg Corr: 0.7857
Epoch [2/20], Step 53500, Train Loss: 0.3959, Val Avg Corr: 0.7946
Epoch [2/20], Step 54000, Train Loss: 0.4034, Val Avg Corr: 0.7849
Epoch [2/20], Step 54500, Train Loss: 0.4248, Val Avg Corr: 0.7866
Epoch [2/20], Step 55000, Train Loss: 0.3388, Val Avg Corr: 0.7886
Epoch [2/20], Step 55500, Train Loss: 0.3475, Val Avg Corr: 0.7887
Epoch [2/20], Step 56000, Train Loss: 0.3532, Val Avg Corr: 0.7884
Epoch [2/20], Step 56500, Train Loss: 0.4850, Val Avg Corr: 0.7916
Epoch [2/20], Step 57000, Train Loss: 0.3866, Val Avg Corr: 0.7893
Epoch [2/20], Step 57500, Train Loss: 0.3890, Val Avg Corr: 0.7938
Epoch [2/20], Step 58000, Train Loss: 0.3447, Val Avg Corr: 0.7930
Epoch [2/20], Step 58500, Train Loss: 0.3398, Val Avg Corr: 0.7904
Epoch [2/20], Step 59000, Train Loss: 0.3360, Val Avg Corr: 0.7921
Epoch [2/20], Step 59500, Train Loss: 0.3370, Val Avg Corr: 0.7899
Epoch [2/20], Step 60000, Train Loss: 0.2973, Val Avg Corr: 0.7854
Epoch [2/20], Step 60500, Train Loss: 0.3828, Val Avg Corr: 0.7842
Epoch [2/20], Step 61000, Train Loss: 0.2831, Val Avg Corr: 0.7867
Epoch [2/20], Step 61500, Train Loss: 0.4109, Val Avg Corr: 0.7835
Trial change detected: 2145 -> 2146, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3228, Val Avg Corr: 0.7925
Epoch [2/20], Step 62500, Train Loss: 0.3769, Val Avg Corr: 0.7967
Epoch [2/20], Step 63000, Train Loss: 0.2927, Val Avg Corr: 0.7933
Epoch [2/20], Step 63500, Train Loss: 0.3709, Val Avg Corr: 0.8018
  >>> New best validation model saved with Avg Corr: 0.8018 <<<
Epoch [2/20], Step 64000, Train Loss: 0.3572, Val Avg Corr: 0.7918
Epoch [2/20], Step 64500, Train Loss: 0.4254, Val Avg Corr: 0.7897
Epoch [2/20], Step 65000, Train Loss: 0.3019, Val Avg Corr: 0.7873
Epoch [2/20], Step 65500, Train Loss: 0.3670, Val Avg Corr: 0.7977
Epoch [3/20], Step 500, Train Loss: 0.3136, Val Avg Corr: 0.7944
Epoch [3/20], Step 1000, Train Loss: 0.4011, Val Avg Corr: 0.7903
Epoch [3/20], Step 1500, Train Loss: 0.4883, Val Avg Corr: 0.7935
Epoch [3/20], Step 2000, Train Loss: 0.3511, Val Avg Corr: 0.7974
Epoch [3/20], Step 2500, Train Loss: 0.2454, Val Avg Corr: 0.8050
  >>> New best validation model saved with Avg Corr: 0.8050 <<<
Epoch [3/20], Step 3000, Train Loss: 0.2911, Val Avg Corr: 0.8009
Epoch [3/20], Step 3500, Train Loss: 0.3640, Val Avg Corr: 0.7867
Epoch [3/20], Step 4000, Train Loss: 0.2923, Val Avg Corr: 0.7953
Epoch [3/20], Step 4500, Train Loss: 0.3530, Val Avg Corr: 0.7982
Epoch [3/20], Step 5000, Train Loss: 0.4609, Val Avg Corr: 0.8017
Epoch [3/20], Step 5500, Train Loss: 0.3025, Val Avg Corr: 0.7971
Epoch [3/20], Step 6000, Train Loss: 0.3686, Val Avg Corr: 0.7974
Epoch [3/20], Step 6500, Train Loss: 0.2336, Val Avg Corr: 0.7954
Epoch [3/20], Step 7000, Train Loss: 0.3247, Val Avg Corr: 0.8012
Epoch [3/20], Step 7500, Train Loss: 0.3467, Val Avg Corr: 0.8002
Epoch [3/20], Step 8000, Train Loss: 0.3343, Val Avg Corr: 0.7936
Epoch [3/20], Step 8500, Train Loss: 0.4273, Val Avg Corr: 0.7879
Epoch [3/20], Step 9000, Train Loss: 0.3317, Val Avg Corr: 0.8005
Epoch [3/20], Step 9500, Train Loss: 0.3589, Val Avg Corr: 0.7980
Epoch [3/20], Step 10000, Train Loss: 0.2592, Val Avg Corr: 0.7885
Epoch [3/20], Step 10500, Train Loss: 0.2399, Val Avg Corr: 0.7843
Epoch [3/20], Step 11000, Train Loss: 0.2933, Val Avg Corr: 0.7882
Epoch [3/20], Step 11500, Train Loss: 0.3155, Val Avg Corr: 0.7873
Epoch [3/20], Step 12000, Train Loss: 0.3532, Val Avg Corr: 0.7966
Epoch [3/20], Step 12500, Train Loss: 0.3687, Val Avg Corr: 0.7962
Epoch [3/20], Step 13000, Train Loss: 0.2981, Val Avg Corr: 0.7962
Epoch [3/20], Step 13500, Train Loss: 0.3641, Val Avg Corr: 0.7933
Epoch [3/20], Step 14000, Train Loss: 0.3572, Val Avg Corr: 0.7899
Epoch [3/20], Step 14500, Train Loss: 0.2821, Val Avg Corr: 0.7973
Epoch [3/20], Step 15000, Train Loss: 0.3278, Val Avg Corr: 0.7951
Epoch [3/20], Step 15500, Train Loss: 0.4485, Val Avg Corr: 0.7955
Epoch [3/20], Step 16000, Train Loss: 0.2938, Val Avg Corr: 0.7923
Epoch [3/20], Step 16500, Train Loss: 0.4195, Val Avg Corr: 0.7959
Epoch [3/20], Step 17000, Train Loss: 0.4025, Val Avg Corr: 0.7976
Epoch [3/20], Step 17500, Train Loss: 0.3338, Val Avg Corr: 0.7913
Epoch [3/20], Step 18000, Train Loss: 0.3767, Val Avg Corr: 0.7927
Epoch [3/20], Step 18500, Train Loss: 0.3966, Val Avg Corr: 0.8016
Epoch [3/20], Step 19000, Train Loss: 0.2878, Val Avg Corr: 0.7988
Epoch [3/20], Step 19500, Train Loss: 0.3861, Val Avg Corr: 0.7944
Epoch [3/20], Step 20000, Train Loss: 0.3102, Val Avg Corr: 0.7981
Epoch [3/20], Step 20500, Train Loss: 0.3264, Val Avg Corr: 0.7953
Trial change detected: 715 -> 716, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.2651, Val Avg Corr: 0.8011
Epoch [3/20], Step 21500, Train Loss: 0.3153, Val Avg Corr: 0.7985
Epoch [3/20], Step 22000, Train Loss: 0.3721, Val Avg Corr: 0.7957
Epoch [3/20], Step 22500, Train Loss: 0.3957, Val Avg Corr: 0.7893
Epoch [3/20], Step 23000, Train Loss: 0.5205, Val Avg Corr: 0.8021
Epoch [3/20], Step 23500, Train Loss: 0.2844, Val Avg Corr: 0.7965
Epoch [3/20], Step 24000, Train Loss: 0.3175, Val Avg Corr: 0.8022
Epoch [3/20], Step 24500, Train Loss: 0.3816, Val Avg Corr: 0.7991
Epoch [3/20], Step 25000, Train Loss: 0.4017, Val Avg Corr: 0.7987
Epoch [3/20], Step 25500, Train Loss: 0.3217, Val Avg Corr: 0.8081
  >>> New best validation model saved with Avg Corr: 0.8081 <<<
Epoch [3/20], Step 26000, Train Loss: 0.3582, Val Avg Corr: 0.8077
Epoch [3/20], Step 26500, Train Loss: 0.2308, Val Avg Corr: 0.8047
Epoch [3/20], Step 27000, Train Loss: 0.2637, Val Avg Corr: 0.8007
Epoch [3/20], Step 27500, Train Loss: 0.3476, Val Avg Corr: 0.7985
Epoch [3/20], Step 28000, Train Loss: 0.3335, Val Avg Corr: 0.7939
Epoch [3/20], Step 28500, Train Loss: 0.3773, Val Avg Corr: 0.7982
Epoch [3/20], Step 29000, Train Loss: 0.3287, Val Avg Corr: 0.8095
  >>> New best validation model saved with Avg Corr: 0.8095 <<<
Epoch [3/20], Step 29500, Train Loss: 0.3089, Val Avg Corr: 0.8002
Epoch [3/20], Step 30000, Train Loss: 0.2610, Val Avg Corr: 0.8044
Epoch [3/20], Step 30500, Train Loss: 0.3287, Val Avg Corr: 0.8055
Epoch [3/20], Step 31000, Train Loss: 0.3851, Val Avg Corr: 0.8083
Epoch [3/20], Step 31500, Train Loss: 0.3283, Val Avg Corr: 0.8122
  >>> New best validation model saved with Avg Corr: 0.8122 <<<
Epoch [3/20], Step 32000, Train Loss: 0.2949, Val Avg Corr: 0.7999
Epoch [3/20], Step 32500, Train Loss: 0.3313, Val Avg Corr: 0.8040
Epoch [3/20], Step 33000, Train Loss: 0.2342, Val Avg Corr: 0.8018
Epoch [3/20], Step 33500, Train Loss: 0.3323, Val Avg Corr: 0.8004
Epoch [3/20], Step 34000, Train Loss: 0.3398, Val Avg Corr: 0.8018
Epoch [3/20], Step 34500, Train Loss: 0.3536, Val Avg Corr: 0.8008
Epoch [3/20], Step 35000, Train Loss: 0.2596, Val Avg Corr: 0.8088
Epoch [3/20], Step 35500, Train Loss: 0.2489, Val Avg Corr: 0.8012
Epoch [3/20], Step 36000, Train Loss: 0.2561, Val Avg Corr: 0.8009
Epoch [3/20], Step 36500, Train Loss: 0.2600, Val Avg Corr: 0.7953
Epoch [3/20], Step 37000, Train Loss: 0.3271, Val Avg Corr: 0.7985
Epoch [3/20], Step 37500, Train Loss: 0.4200, Val Avg Corr: 0.8073
Epoch [3/20], Step 38000, Train Loss: 0.3643, Val Avg Corr: 0.8032
Epoch [3/20], Step 38500, Train Loss: 0.3833, Val Avg Corr: 0.8009
Epoch [3/20], Step 39000, Train Loss: 0.2718, Val Avg Corr: 0.8094
Epoch [3/20], Step 39500, Train Loss: 0.2767, Val Avg Corr: 0.8089
Epoch [3/20], Step 40000, Train Loss: 0.3540, Val Avg Corr: 0.8059
Epoch [3/20], Step 40500, Train Loss: 0.2833, Val Avg Corr: 0.8012
Epoch [3/20], Step 41000, Train Loss: 0.2384, Val Avg Corr: 0.7982
Trial change detected: 1438 -> 1439, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.3385, Val Avg Corr: 0.8069
Epoch [3/20], Step 42000, Train Loss: 0.3039, Val Avg Corr: 0.8052
Epoch [3/20], Step 42500, Train Loss: 0.3208, Val Avg Corr: 0.8030
Epoch [3/20], Step 43000, Train Loss: 0.2821, Val Avg Corr: 0.8084
Epoch [3/20], Step 43500, Train Loss: 0.2842, Val Avg Corr: 0.8035
Epoch [3/20], Step 44000, Train Loss: 0.3269, Val Avg Corr: 0.8037
Epoch [3/20], Step 44500, Train Loss: 0.3214, Val Avg Corr: 0.8055
Epoch [3/20], Step 45000, Train Loss: 0.3420, Val Avg Corr: 0.8027
Epoch [3/20], Step 45500, Train Loss: 0.3638, Val Avg Corr: 0.8092
Epoch [3/20], Step 46000, Train Loss: 0.3376, Val Avg Corr: 0.8051
Epoch [3/20], Step 46500, Train Loss: 0.2609, Val Avg Corr: 0.8019
Epoch [3/20], Step 47000, Train Loss: 0.2234, Val Avg Corr: 0.8075
Epoch [3/20], Step 47500, Train Loss: 0.3450, Val Avg Corr: 0.8056
Epoch [3/20], Step 48000, Train Loss: 0.3013, Val Avg Corr: 0.8076
Epoch [3/20], Step 48500, Train Loss: 0.4006, Val Avg Corr: 0.8094
Epoch [3/20], Step 49000, Train Loss: 0.3511, Val Avg Corr: 0.8078
Epoch [3/20], Step 49500, Train Loss: 0.2451, Val Avg Corr: 0.8006
Epoch [3/20], Step 50000, Train Loss: 0.3206, Val Avg Corr: 0.7996
Epoch [3/20], Step 50500, Train Loss: 0.3724, Val Avg Corr: 0.8073
Epoch [3/20], Step 51000, Train Loss: 0.2937, Val Avg Corr: 0.8050
Epoch [3/20], Step 51500, Train Loss: 0.2811, Val Avg Corr: 0.8053
Epoch [3/20], Step 52000, Train Loss: 0.2931, Val Avg Corr: 0.8027
Epoch [3/20], Step 52500, Train Loss: 0.3478, Val Avg Corr: 0.8093
Epoch [3/20], Step 53000, Train Loss: 0.3527, Val Avg Corr: 0.8012
Epoch [3/20], Step 53500, Train Loss: 0.3777, Val Avg Corr: 0.8037
Epoch [3/20], Step 54000, Train Loss: 0.3982, Val Avg Corr: 0.7991
Epoch [3/20], Step 54500, Train Loss: 0.3872, Val Avg Corr: 0.8020
Epoch [3/20], Step 55000, Train Loss: 0.2881, Val Avg Corr: 0.8036
Epoch [3/20], Step 55500, Train Loss: 0.3138, Val Avg Corr: 0.8005
Epoch [3/20], Step 56000, Train Loss: 0.3173, Val Avg Corr: 0.8028
Epoch [3/20], Step 56500, Train Loss: 0.4363, Val Avg Corr: 0.8054
Early stopping triggered after 56500 steps in epoch 3.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8122
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8357, Y=0.8057, Avg=0.8207

--- Running SNN Online Training ---
  Input size: 182, Train: 65846, Val: 14104, Test: 14145
Initializing updater with Hebbian (error × d_lif × activity)

=== PRE-SNN VERIFICATION (Session 10) ===
Train counts shape: (65846, 182), dtype: float32
Sample train counts (5x10 matrix):
Row 0:    0.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 1:    0.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 2:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 3:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Row 4:    0.0    1.0    1.0    0.0    0.0    0.0    0.0    0.0    0.0    0.0
Are train counts integers? True
Starting SNN Online Training for 20 epochs on cuda:0...
Evaluation every 500 steps, reset states every never steps
Warm-starting RMS EMAs with 50 steps...
RMS EMA warm-start complete.
Epoch [1/20], Step 500, Train Loss: 1.1889, Val Avg Corr: 0.0377
  >>> New best validation model saved with Avg Corr: 0.0377 <<<
Epoch [1/20], Step 1000, Train Loss: 1.1435, Val Avg Corr: 0.0203
Epoch [1/20], Step 1500, Train Loss: 1.0317, Val Avg Corr: 0.0779
  >>> New best validation model saved with Avg Corr: 0.0779 <<<
Epoch [1/20], Step 2000, Train Loss: 0.8436, Val Avg Corr: 0.1190
  >>> New best validation model saved with Avg Corr: 0.1190 <<<
Epoch [1/20], Step 2500, Train Loss: 1.0509, Val Avg Corr: 0.1237
  >>> New best validation model saved with Avg Corr: 0.1237 <<<
Epoch [1/20], Step 3000, Train Loss: 1.0112, Val Avg Corr: 0.1471
  >>> New best validation model saved with Avg Corr: 0.1471 <<<
Epoch [1/20], Step 3500, Train Loss: 0.7883, Val Avg Corr: 0.1791
  >>> New best validation model saved with Avg Corr: 0.1791 <<<
Epoch [1/20], Step 4000, Train Loss: 0.8209, Val Avg Corr: 0.2363
  >>> New best validation model saved with Avg Corr: 0.2363 <<<
Epoch [1/20], Step 4500, Train Loss: 0.9398, Val Avg Corr: 0.2402
  >>> New best validation model saved with Avg Corr: 0.2402 <<<
Epoch [1/20], Step 5000, Train Loss: 1.0456, Val Avg Corr: 0.2866
  >>> New best validation model saved with Avg Corr: 0.2866 <<<
Epoch [1/20], Step 5500, Train Loss: 0.8309, Val Avg Corr: 0.3119
  >>> New best validation model saved with Avg Corr: 0.3119 <<<
Epoch [1/20], Step 6000, Train Loss: 0.7555, Val Avg Corr: 0.3217
  >>> New best validation model saved with Avg Corr: 0.3217 <<<
Epoch [1/20], Step 6500, Train Loss: 0.8495, Val Avg Corr: 0.3252
  >>> New best validation model saved with Avg Corr: 0.3252 <<<
Epoch [1/20], Step 7000, Train Loss: 0.8191, Val Avg Corr: 0.3715
  >>> New best validation model saved with Avg Corr: 0.3715 <<<
Epoch [1/20], Step 7500, Train Loss: 0.9302, Val Avg Corr: 0.3711
Epoch [1/20], Step 8000, Train Loss: 0.8233, Val Avg Corr: 0.4029
  >>> New best validation model saved with Avg Corr: 0.4029 <<<
Epoch [1/20], Step 8500, Train Loss: 0.7418, Val Avg Corr: 0.4199
  >>> New best validation model saved with Avg Corr: 0.4199 <<<
Epoch [1/20], Step 9000, Train Loss: 0.7500, Val Avg Corr: 0.4516
  >>> New best validation model saved with Avg Corr: 0.4516 <<<
Epoch [1/20], Step 9500, Train Loss: 0.7861, Val Avg Corr: 0.4383
Epoch [1/20], Step 10000, Train Loss: 0.7700, Val Avg Corr: 0.4532
  >>> New best validation model saved with Avg Corr: 0.4532 <<<
Epoch [1/20], Step 10500, Train Loss: 0.7810, Val Avg Corr: 0.4447
Epoch [1/20], Step 11000, Train Loss: 0.8294, Val Avg Corr: 0.4341
Epoch [1/20], Step 11500, Train Loss: 1.0055, Val Avg Corr: 0.4698
  >>> New best validation model saved with Avg Corr: 0.4698 <<<
Epoch [1/20], Step 12000, Train Loss: 0.6435, Val Avg Corr: 0.5024
  >>> New best validation model saved with Avg Corr: 0.5024 <<<
Epoch [1/20], Step 12500, Train Loss: 0.6706, Val Avg Corr: 0.5249
  >>> New best validation model saved with Avg Corr: 0.5249 <<<
Epoch [1/20], Step 13000, Train Loss: 0.7425, Val Avg Corr: 0.5453
  >>> New best validation model saved with Avg Corr: 0.5453 <<<
Epoch [1/20], Step 13500, Train Loss: 0.7930, Val Avg Corr: 0.5551
  >>> New best validation model saved with Avg Corr: 0.5551 <<<
Epoch [1/20], Step 14000, Train Loss: 0.8195, Val Avg Corr: 0.5655
  >>> New best validation model saved with Avg Corr: 0.5655 <<<
Epoch [1/20], Step 14500, Train Loss: 0.5979, Val Avg Corr: 0.5755
  >>> New best validation model saved with Avg Corr: 0.5755 <<<
Epoch [1/20], Step 15000, Train Loss: 0.7329, Val Avg Corr: 0.5715
Epoch [1/20], Step 15500, Train Loss: 0.6439, Val Avg Corr: 0.5849
  >>> New best validation model saved with Avg Corr: 0.5849 <<<
Epoch [1/20], Step 16000, Train Loss: 0.5253, Val Avg Corr: 0.5989
  >>> New best validation model saved with Avg Corr: 0.5989 <<<
Epoch [1/20], Step 16500, Train Loss: 0.7927, Val Avg Corr: 0.6018
  >>> New best validation model saved with Avg Corr: 0.6018 <<<
Epoch [1/20], Step 17000, Train Loss: 0.6650, Val Avg Corr: 0.6137
  >>> New best validation model saved with Avg Corr: 0.6137 <<<
Epoch [1/20], Step 17500, Train Loss: 0.5146, Val Avg Corr: 0.5979
Epoch [1/20], Step 18000, Train Loss: 0.6593, Val Avg Corr: 0.5954
Epoch [1/20], Step 18500, Train Loss: 0.6369, Val Avg Corr: 0.6328
  >>> New best validation model saved with Avg Corr: 0.6328 <<<
Epoch [1/20], Step 19000, Train Loss: 0.6297, Val Avg Corr: 0.6391
  >>> New best validation model saved with Avg Corr: 0.6391 <<<
Epoch [1/20], Step 19500, Train Loss: 0.5878, Val Avg Corr: 0.6516
  >>> New best validation model saved with Avg Corr: 0.6516 <<<
Epoch [1/20], Step 20000, Train Loss: 0.5691, Val Avg Corr: 0.6491
Epoch [1/20], Step 20500, Train Loss: 0.6437, Val Avg Corr: 0.6462
Trial change detected: 711 -> 712, resetting states
Epoch [1/20], Step 21000, Train Loss: 0.4721, Val Avg Corr: 0.6507
Epoch [1/20], Step 21500, Train Loss: 0.6239, Val Avg Corr: 0.6615
  >>> New best validation model saved with Avg Corr: 0.6615 <<<
Epoch [1/20], Step 22000, Train Loss: 0.5303, Val Avg Corr: 0.6642
  >>> New best validation model saved with Avg Corr: 0.6642 <<<
Epoch [1/20], Step 22500, Train Loss: 0.6248, Val Avg Corr: 0.6779
  >>> New best validation model saved with Avg Corr: 0.6779 <<<
Epoch [1/20], Step 23000, Train Loss: 0.5598, Val Avg Corr: 0.6651
Epoch [1/20], Step 23500, Train Loss: 0.4659, Val Avg Corr: 0.6736
Epoch [1/20], Step 24000, Train Loss: 0.6505, Val Avg Corr: 0.6816
  >>> New best validation model saved with Avg Corr: 0.6816 <<<
Epoch [1/20], Step 24500, Train Loss: 0.5340, Val Avg Corr: 0.6850
  >>> New best validation model saved with Avg Corr: 0.6850 <<<
Epoch [1/20], Step 25000, Train Loss: 0.5303, Val Avg Corr: 0.6819
Epoch [1/20], Step 25500, Train Loss: 0.4913, Val Avg Corr: 0.6846
Epoch [1/20], Step 26000, Train Loss: 0.3522, Val Avg Corr: 0.6981
  >>> New best validation model saved with Avg Corr: 0.6981 <<<
Epoch [1/20], Step 26500, Train Loss: 0.3652, Val Avg Corr: 0.7028
  >>> New best validation model saved with Avg Corr: 0.7028 <<<
Epoch [1/20], Step 27000, Train Loss: 0.3865, Val Avg Corr: 0.6986
Epoch [1/20], Step 27500, Train Loss: 0.4661, Val Avg Corr: 0.7040
  >>> New best validation model saved with Avg Corr: 0.7040 <<<
Epoch [1/20], Step 28000, Train Loss: 0.5020, Val Avg Corr: 0.7134
  >>> New best validation model saved with Avg Corr: 0.7134 <<<
Epoch [1/20], Step 28500, Train Loss: 0.4268, Val Avg Corr: 0.7129
Epoch [1/20], Step 29000, Train Loss: 0.4347, Val Avg Corr: 0.7146
  >>> New best validation model saved with Avg Corr: 0.7146 <<<
Epoch [1/20], Step 29500, Train Loss: 0.5095, Val Avg Corr: 0.7229
  >>> New best validation model saved with Avg Corr: 0.7229 <<<
Epoch [1/20], Step 30000, Train Loss: 0.4525, Val Avg Corr: 0.7218
Epoch [1/20], Step 30500, Train Loss: 0.4607, Val Avg Corr: 0.7255
  >>> New best validation model saved with Avg Corr: 0.7255 <<<
Epoch [1/20], Step 31000, Train Loss: 0.4435, Val Avg Corr: 0.7211
Epoch [1/20], Step 31500, Train Loss: 0.3924, Val Avg Corr: 0.7354
  >>> New best validation model saved with Avg Corr: 0.7354 <<<
Epoch [1/20], Step 32000, Train Loss: 0.3946, Val Avg Corr: 0.7351
Epoch [1/20], Step 32500, Train Loss: 0.3957, Val Avg Corr: 0.7375
  >>> New best validation model saved with Avg Corr: 0.7375 <<<
Epoch [1/20], Step 33000, Train Loss: 0.4386, Val Avg Corr: 0.7328
Epoch [1/20], Step 33500, Train Loss: 0.4552, Val Avg Corr: 0.7433
  >>> New best validation model saved with Avg Corr: 0.7433 <<<
Epoch [1/20], Step 34000, Train Loss: 0.3762, Val Avg Corr: 0.7386
Epoch [1/20], Step 34500, Train Loss: 0.3647, Val Avg Corr: 0.7465
  >>> New best validation model saved with Avg Corr: 0.7465 <<<
Epoch [1/20], Step 35000, Train Loss: 0.3481, Val Avg Corr: 0.7452
Epoch [1/20], Step 35500, Train Loss: 0.4475, Val Avg Corr: 0.7499
  >>> New best validation model saved with Avg Corr: 0.7499 <<<
Epoch [1/20], Step 36000, Train Loss: 0.4154, Val Avg Corr: 0.7579
  >>> New best validation model saved with Avg Corr: 0.7579 <<<
Epoch [1/20], Step 36500, Train Loss: 0.2931, Val Avg Corr: 0.7480
Epoch [1/20], Step 37000, Train Loss: 0.5567, Val Avg Corr: 0.7550
Epoch [1/20], Step 37500, Train Loss: 0.5780, Val Avg Corr: 0.7519
Epoch [1/20], Step 38000, Train Loss: 0.4666, Val Avg Corr: 0.7586
  >>> New best validation model saved with Avg Corr: 0.7586 <<<
Epoch [1/20], Step 38500, Train Loss: 0.4161, Val Avg Corr: 0.7560
Epoch [1/20], Step 39000, Train Loss: 0.4178, Val Avg Corr: 0.7604
  >>> New best validation model saved with Avg Corr: 0.7604 <<<
Epoch [1/20], Step 39500, Train Loss: 0.3911, Val Avg Corr: 0.7583
Epoch [1/20], Step 40000, Train Loss: 0.5938, Val Avg Corr: 0.7613
  >>> New best validation model saved with Avg Corr: 0.7613 <<<
Epoch [1/20], Step 40500, Train Loss: 0.3743, Val Avg Corr: 0.7593
Epoch [1/20], Step 41000, Train Loss: 0.4508, Val Avg Corr: 0.7641
  >>> New best validation model saved with Avg Corr: 0.7641 <<<
Trial change detected: 1450 -> 1451, resetting states
Epoch [1/20], Step 41500, Train Loss: 0.4283, Val Avg Corr: 0.7601
Epoch [1/20], Step 42000, Train Loss: 0.3252, Val Avg Corr: 0.7610
Epoch [1/20], Step 42500, Train Loss: 0.4302, Val Avg Corr: 0.7669
  >>> New best validation model saved with Avg Corr: 0.7669 <<<
Epoch [1/20], Step 43000, Train Loss: 0.4231, Val Avg Corr: 0.7652
Epoch [1/20], Step 43500, Train Loss: 0.4443, Val Avg Corr: 0.7630
Epoch [1/20], Step 44000, Train Loss: 0.4019, Val Avg Corr: 0.7717
  >>> New best validation model saved with Avg Corr: 0.7717 <<<
Epoch [1/20], Step 44500, Train Loss: 0.4355, Val Avg Corr: 0.7669
Epoch [1/20], Step 45000, Train Loss: 0.4823, Val Avg Corr: 0.7759
  >>> New best validation model saved with Avg Corr: 0.7759 <<<
Epoch [1/20], Step 45500, Train Loss: 0.3303, Val Avg Corr: 0.7723
Epoch [1/20], Step 46000, Train Loss: 0.5064, Val Avg Corr: 0.7834
  >>> New best validation model saved with Avg Corr: 0.7834 <<<
Epoch [1/20], Step 46500, Train Loss: 0.3579, Val Avg Corr: 0.7825
Epoch [1/20], Step 47000, Train Loss: 0.3783, Val Avg Corr: 0.7835
  >>> New best validation model saved with Avg Corr: 0.7835 <<<
Epoch [1/20], Step 47500, Train Loss: 0.4030, Val Avg Corr: 0.7856
  >>> New best validation model saved with Avg Corr: 0.7856 <<<
Epoch [1/20], Step 48000, Train Loss: 0.4407, Val Avg Corr: 0.7873
  >>> New best validation model saved with Avg Corr: 0.7873 <<<
Epoch [1/20], Step 48500, Train Loss: 0.5058, Val Avg Corr: 0.7883
  >>> New best validation model saved with Avg Corr: 0.7883 <<<
Epoch [1/20], Step 49000, Train Loss: 0.4074, Val Avg Corr: 0.7760
Epoch [1/20], Step 49500, Train Loss: 0.3499, Val Avg Corr: 0.7843
Epoch [1/20], Step 50000, Train Loss: 0.4123, Val Avg Corr: 0.7857
Epoch [1/20], Step 50500, Train Loss: 0.3709, Val Avg Corr: 0.7808
Epoch [1/20], Step 51000, Train Loss: 0.3873, Val Avg Corr: 0.7893
  >>> New best validation model saved with Avg Corr: 0.7893 <<<
Epoch [1/20], Step 51500, Train Loss: 0.3839, Val Avg Corr: 0.7879
Epoch [1/20], Step 52000, Train Loss: 0.4279, Val Avg Corr: 0.7827
Epoch [1/20], Step 52500, Train Loss: 0.4374, Val Avg Corr: 0.7894
  >>> New best validation model saved with Avg Corr: 0.7894 <<<
Epoch [1/20], Step 53000, Train Loss: 0.3960, Val Avg Corr: 0.7880
Epoch [1/20], Step 53500, Train Loss: 0.3968, Val Avg Corr: 0.7892
Epoch [1/20], Step 54000, Train Loss: 0.4513, Val Avg Corr: 0.7848
Epoch [1/20], Step 54500, Train Loss: 0.4031, Val Avg Corr: 0.7891
Epoch [1/20], Step 55000, Train Loss: 0.3868, Val Avg Corr: 0.7899
  >>> New best validation model saved with Avg Corr: 0.7899 <<<
Epoch [1/20], Step 55500, Train Loss: 0.4322, Val Avg Corr: 0.7892
Epoch [1/20], Step 56000, Train Loss: 0.3946, Val Avg Corr: 0.7856
Epoch [1/20], Step 56500, Train Loss: 0.4470, Val Avg Corr: 0.7888
Epoch [1/20], Step 57000, Train Loss: 0.4546, Val Avg Corr: 0.7964
  >>> New best validation model saved with Avg Corr: 0.7964 <<<
Epoch [1/20], Step 57500, Train Loss: 0.3562, Val Avg Corr: 0.7925
Epoch [1/20], Step 58000, Train Loss: 0.3479, Val Avg Corr: 0.7971
  >>> New best validation model saved with Avg Corr: 0.7971 <<<
Epoch [1/20], Step 58500, Train Loss: 0.4334, Val Avg Corr: 0.7924
Epoch [1/20], Step 59000, Train Loss: 0.3727, Val Avg Corr: 0.7938
Epoch [1/20], Step 59500, Train Loss: 0.3839, Val Avg Corr: 0.7975
  >>> New best validation model saved with Avg Corr: 0.7975 <<<
Epoch [1/20], Step 60000, Train Loss: 0.3969, Val Avg Corr: 0.7914
Epoch [1/20], Step 60500, Train Loss: 0.4367, Val Avg Corr: 0.7982
  >>> New best validation model saved with Avg Corr: 0.7982 <<<
Epoch [1/20], Step 61000, Train Loss: 0.3745, Val Avg Corr: 0.7983
  >>> New best validation model saved with Avg Corr: 0.7983 <<<
Epoch [1/20], Step 61500, Train Loss: 0.4217, Val Avg Corr: 0.8033
  >>> New best validation model saved with Avg Corr: 0.8033 <<<
Trial change detected: 2156 -> 2157, resetting states
Epoch [1/20], Step 62000, Train Loss: 0.4245, Val Avg Corr: 0.7982
Epoch [1/20], Step 62500, Train Loss: 0.2731, Val Avg Corr: 0.7978
Epoch [1/20], Step 63000, Train Loss: 0.4696, Val Avg Corr: 0.8055
  >>> New best validation model saved with Avg Corr: 0.8055 <<<
Epoch [1/20], Step 63500, Train Loss: 0.4162, Val Avg Corr: 0.7994
Epoch [1/20], Step 64000, Train Loss: 0.3514, Val Avg Corr: 0.7946
Epoch [1/20], Step 64500, Train Loss: 0.3559, Val Avg Corr: 0.8003
Epoch [1/20], Step 65000, Train Loss: 0.3522, Val Avg Corr: 0.7983
Epoch [1/20], Step 65500, Train Loss: 0.3540, Val Avg Corr: 0.8018
Epoch [2/20], Step 500, Train Loss: 0.4112, Val Avg Corr: 0.8088
  >>> New best validation model saved with Avg Corr: 0.8088 <<<
Epoch [2/20], Step 1000, Train Loss: 0.5814, Val Avg Corr: 0.8065
Epoch [2/20], Step 1500, Train Loss: 0.4884, Val Avg Corr: 0.8074
Epoch [2/20], Step 2000, Train Loss: 0.2823, Val Avg Corr: 0.8023
Epoch [2/20], Step 2500, Train Loss: 0.3521, Val Avg Corr: 0.8018
Epoch [2/20], Step 3000, Train Loss: 0.4105, Val Avg Corr: 0.8010
Epoch [2/20], Step 3500, Train Loss: 0.2853, Val Avg Corr: 0.8064
Epoch [2/20], Step 4000, Train Loss: 0.3350, Val Avg Corr: 0.7956
Epoch [2/20], Step 4500, Train Loss: 0.3995, Val Avg Corr: 0.8040
Epoch [2/20], Step 5000, Train Loss: 0.4205, Val Avg Corr: 0.8027
Epoch [2/20], Step 5500, Train Loss: 0.3212, Val Avg Corr: 0.8014
Epoch [2/20], Step 6000, Train Loss: 0.3334, Val Avg Corr: 0.8175
  >>> New best validation model saved with Avg Corr: 0.8175 <<<
Epoch [2/20], Step 6500, Train Loss: 0.3115, Val Avg Corr: 0.8070
Epoch [2/20], Step 7000, Train Loss: 0.4360, Val Avg Corr: 0.8097
Epoch [2/20], Step 7500, Train Loss: 0.3617, Val Avg Corr: 0.8044
Epoch [2/20], Step 8000, Train Loss: 0.4131, Val Avg Corr: 0.8035
Epoch [2/20], Step 8500, Train Loss: 0.3130, Val Avg Corr: 0.8090
Epoch [2/20], Step 9000, Train Loss: 0.3055, Val Avg Corr: 0.8084
Epoch [2/20], Step 9500, Train Loss: 0.3129, Val Avg Corr: 0.8037
Epoch [2/20], Step 10000, Train Loss: 0.3328, Val Avg Corr: 0.8007
Epoch [2/20], Step 10500, Train Loss: 0.3284, Val Avg Corr: 0.8069
Epoch [2/20], Step 11000, Train Loss: 0.3673, Val Avg Corr: 0.8065
Epoch [2/20], Step 11500, Train Loss: 0.3766, Val Avg Corr: 0.8041
Epoch [2/20], Step 12000, Train Loss: 0.3277, Val Avg Corr: 0.8083
Epoch [2/20], Step 12500, Train Loss: 0.3291, Val Avg Corr: 0.8131
Epoch [2/20], Step 13000, Train Loss: 0.3502, Val Avg Corr: 0.8139
Epoch [2/20], Step 13500, Train Loss: 0.3748, Val Avg Corr: 0.8118
Epoch [2/20], Step 14000, Train Loss: 0.3187, Val Avg Corr: 0.8110
Epoch [2/20], Step 14500, Train Loss: 0.2836, Val Avg Corr: 0.8152
Epoch [2/20], Step 15000, Train Loss: 0.4267, Val Avg Corr: 0.8042
Epoch [2/20], Step 15500, Train Loss: 0.3880, Val Avg Corr: 0.8070
Epoch [2/20], Step 16000, Train Loss: 0.2837, Val Avg Corr: 0.8125
Epoch [2/20], Step 16500, Train Loss: 0.4056, Val Avg Corr: 0.8006
Epoch [2/20], Step 17000, Train Loss: 0.3667, Val Avg Corr: 0.8091
Epoch [2/20], Step 17500, Train Loss: 0.2834, Val Avg Corr: 0.8053
Epoch [2/20], Step 18000, Train Loss: 0.4235, Val Avg Corr: 0.8131
Epoch [2/20], Step 18500, Train Loss: 0.4410, Val Avg Corr: 0.8151
Epoch [2/20], Step 19000, Train Loss: 0.4251, Val Avg Corr: 0.8123
Epoch [2/20], Step 19500, Train Loss: 0.4087, Val Avg Corr: 0.8124
Epoch [2/20], Step 20000, Train Loss: 0.3425, Val Avg Corr: 0.8102
Epoch [2/20], Step 20500, Train Loss: 0.4237, Val Avg Corr: 0.8144
Trial change detected: 711 -> 712, resetting states
Epoch [2/20], Step 21000, Train Loss: 0.2782, Val Avg Corr: 0.8058
Epoch [2/20], Step 21500, Train Loss: 0.3919, Val Avg Corr: 0.8128
Epoch [2/20], Step 22000, Train Loss: 0.3498, Val Avg Corr: 0.8098
Epoch [2/20], Step 22500, Train Loss: 0.4467, Val Avg Corr: 0.8100
Epoch [2/20], Step 23000, Train Loss: 0.4003, Val Avg Corr: 0.8111
Epoch [2/20], Step 23500, Train Loss: 0.2947, Val Avg Corr: 0.8100
Epoch [2/20], Step 24000, Train Loss: 0.4606, Val Avg Corr: 0.8168
Epoch [2/20], Step 24500, Train Loss: 0.3718, Val Avg Corr: 0.8161
Epoch [2/20], Step 25000, Train Loss: 0.3737, Val Avg Corr: 0.8129
Epoch [2/20], Step 25500, Train Loss: 0.2836, Val Avg Corr: 0.8111
Epoch [2/20], Step 26000, Train Loss: 0.2567, Val Avg Corr: 0.8143
Epoch [2/20], Step 26500, Train Loss: 0.2787, Val Avg Corr: 0.8166
Epoch [2/20], Step 27000, Train Loss: 0.2585, Val Avg Corr: 0.8100
Epoch [2/20], Step 27500, Train Loss: 0.3695, Val Avg Corr: 0.8172
Epoch [2/20], Step 28000, Train Loss: 0.3757, Val Avg Corr: 0.8109
Epoch [2/20], Step 28500, Train Loss: 0.3264, Val Avg Corr: 0.8136
Epoch [2/20], Step 29000, Train Loss: 0.3276, Val Avg Corr: 0.8179
  >>> New best validation model saved with Avg Corr: 0.8179 <<<
Epoch [2/20], Step 29500, Train Loss: 0.3345, Val Avg Corr: 0.8187
  >>> New best validation model saved with Avg Corr: 0.8187 <<<
Epoch [2/20], Step 30000, Train Loss: 0.3341, Val Avg Corr: 0.8207
  >>> New best validation model saved with Avg Corr: 0.8207 <<<
Epoch [2/20], Step 30500, Train Loss: 0.3769, Val Avg Corr: 0.8176
Epoch [2/20], Step 31000, Train Loss: 0.3208, Val Avg Corr: 0.8245
  >>> New best validation model saved with Avg Corr: 0.8245 <<<
Epoch [2/20], Step 31500, Train Loss: 0.3202, Val Avg Corr: 0.8229
Epoch [2/20], Step 32000, Train Loss: 0.2918, Val Avg Corr: 0.8206
Epoch [2/20], Step 32500, Train Loss: 0.3411, Val Avg Corr: 0.8164
Epoch [2/20], Step 33000, Train Loss: 0.3143, Val Avg Corr: 0.8252
  >>> New best validation model saved with Avg Corr: 0.8252 <<<
Epoch [2/20], Step 33500, Train Loss: 0.3884, Val Avg Corr: 0.8217
Epoch [2/20], Step 34000, Train Loss: 0.2701, Val Avg Corr: 0.8241
Epoch [2/20], Step 34500, Train Loss: 0.2907, Val Avg Corr: 0.8237
Epoch [2/20], Step 35000, Train Loss: 0.2945, Val Avg Corr: 0.8203
Epoch [2/20], Step 35500, Train Loss: 0.2927, Val Avg Corr: 0.8241
Epoch [2/20], Step 36000, Train Loss: 0.2935, Val Avg Corr: 0.8204
Epoch [2/20], Step 36500, Train Loss: 0.2269, Val Avg Corr: 0.8179
Epoch [2/20], Step 37000, Train Loss: 0.4357, Val Avg Corr: 0.8206
Epoch [2/20], Step 37500, Train Loss: 0.4397, Val Avg Corr: 0.8228
Epoch [2/20], Step 38000, Train Loss: 0.3598, Val Avg Corr: 0.8187
Epoch [2/20], Step 38500, Train Loss: 0.3291, Val Avg Corr: 0.8154
Epoch [2/20], Step 39000, Train Loss: 0.3487, Val Avg Corr: 0.8149
Epoch [2/20], Step 39500, Train Loss: 0.3303, Val Avg Corr: 0.8216
Epoch [2/20], Step 40000, Train Loss: 0.4852, Val Avg Corr: 0.8196
Epoch [2/20], Step 40500, Train Loss: 0.2893, Val Avg Corr: 0.8253
  >>> New best validation model saved with Avg Corr: 0.8253 <<<
Epoch [2/20], Step 41000, Train Loss: 0.3535, Val Avg Corr: 0.8206
Trial change detected: 1450 -> 1451, resetting states
Epoch [2/20], Step 41500, Train Loss: 0.3672, Val Avg Corr: 0.8238
Epoch [2/20], Step 42000, Train Loss: 0.2604, Val Avg Corr: 0.8194
Epoch [2/20], Step 42500, Train Loss: 0.3384, Val Avg Corr: 0.8240
Epoch [2/20], Step 43000, Train Loss: 0.3427, Val Avg Corr: 0.8220
Epoch [2/20], Step 43500, Train Loss: 0.3901, Val Avg Corr: 0.8258
  >>> New best validation model saved with Avg Corr: 0.8258 <<<
Epoch [2/20], Step 44000, Train Loss: 0.3351, Val Avg Corr: 0.8212
Epoch [2/20], Step 44500, Train Loss: 0.3908, Val Avg Corr: 0.8210
Epoch [2/20], Step 45000, Train Loss: 0.3714, Val Avg Corr: 0.8240
Epoch [2/20], Step 45500, Train Loss: 0.2684, Val Avg Corr: 0.8223
Epoch [2/20], Step 46000, Train Loss: 0.4148, Val Avg Corr: 0.8284
  >>> New best validation model saved with Avg Corr: 0.8284 <<<
Epoch [2/20], Step 46500, Train Loss: 0.2893, Val Avg Corr: 0.8239
Epoch [2/20], Step 47000, Train Loss: 0.2926, Val Avg Corr: 0.8238
Epoch [2/20], Step 47500, Train Loss: 0.3570, Val Avg Corr: 0.8265
Epoch [2/20], Step 48000, Train Loss: 0.3578, Val Avg Corr: 0.8264
Epoch [2/20], Step 48500, Train Loss: 0.4294, Val Avg Corr: 0.8306
  >>> New best validation model saved with Avg Corr: 0.8306 <<<
Epoch [2/20], Step 49000, Train Loss: 0.3237, Val Avg Corr: 0.8241
Epoch [2/20], Step 49500, Train Loss: 0.3070, Val Avg Corr: 0.8314
  >>> New best validation model saved with Avg Corr: 0.8314 <<<
Epoch [2/20], Step 50000, Train Loss: 0.3630, Val Avg Corr: 0.8332
  >>> New best validation model saved with Avg Corr: 0.8332 <<<
Epoch [2/20], Step 50500, Train Loss: 0.3125, Val Avg Corr: 0.8260
Epoch [2/20], Step 51000, Train Loss: 0.3170, Val Avg Corr: 0.8330
Epoch [2/20], Step 51500, Train Loss: 0.2822, Val Avg Corr: 0.8285
Epoch [2/20], Step 52000, Train Loss: 0.3691, Val Avg Corr: 0.8294
Epoch [2/20], Step 52500, Train Loss: 0.3488, Val Avg Corr: 0.8265
Epoch [2/20], Step 53000, Train Loss: 0.3314, Val Avg Corr: 0.8283
Epoch [2/20], Step 53500, Train Loss: 0.3585, Val Avg Corr: 0.8297
Epoch [2/20], Step 54000, Train Loss: 0.4072, Val Avg Corr: 0.8202
Epoch [2/20], Step 54500, Train Loss: 0.3203, Val Avg Corr: 0.8284
Epoch [2/20], Step 55000, Train Loss: 0.3303, Val Avg Corr: 0.8298
Epoch [2/20], Step 55500, Train Loss: 0.3788, Val Avg Corr: 0.8317
Epoch [2/20], Step 56000, Train Loss: 0.3413, Val Avg Corr: 0.8268
Epoch [2/20], Step 56500, Train Loss: 0.3594, Val Avg Corr: 0.8217
Epoch [2/20], Step 57000, Train Loss: 0.3987, Val Avg Corr: 0.8281
Epoch [2/20], Step 57500, Train Loss: 0.3182, Val Avg Corr: 0.8276
Epoch [2/20], Step 58000, Train Loss: 0.3005, Val Avg Corr: 0.8255
Epoch [2/20], Step 58500, Train Loss: 0.3811, Val Avg Corr: 0.8234
Epoch [2/20], Step 59000, Train Loss: 0.3306, Val Avg Corr: 0.8236
Epoch [2/20], Step 59500, Train Loss: 0.3081, Val Avg Corr: 0.8288
Epoch [2/20], Step 60000, Train Loss: 0.3589, Val Avg Corr: 0.8261
Epoch [2/20], Step 60500, Train Loss: 0.3935, Val Avg Corr: 0.8284
Epoch [2/20], Step 61000, Train Loss: 0.3315, Val Avg Corr: 0.8306
Epoch [2/20], Step 61500, Train Loss: 0.3685, Val Avg Corr: 0.8318
Trial change detected: 2156 -> 2157, resetting states
Epoch [2/20], Step 62000, Train Loss: 0.3502, Val Avg Corr: 0.8341
  >>> New best validation model saved with Avg Corr: 0.8341 <<<
Epoch [2/20], Step 62500, Train Loss: 0.2697, Val Avg Corr: 0.8315
Epoch [2/20], Step 63000, Train Loss: 0.4173, Val Avg Corr: 0.8376
  >>> New best validation model saved with Avg Corr: 0.8376 <<<
Epoch [2/20], Step 63500, Train Loss: 0.3330, Val Avg Corr: 0.8309
Epoch [2/20], Step 64000, Train Loss: 0.3022, Val Avg Corr: 0.8279
Epoch [2/20], Step 64500, Train Loss: 0.3150, Val Avg Corr: 0.8283
Epoch [2/20], Step 65000, Train Loss: 0.3420, Val Avg Corr: 0.8339
Epoch [2/20], Step 65500, Train Loss: 0.2973, Val Avg Corr: 0.8299
Epoch [3/20], Step 500, Train Loss: 0.3688, Val Avg Corr: 0.8360
Epoch [3/20], Step 1000, Train Loss: 0.5309, Val Avg Corr: 0.8299
Epoch [3/20], Step 1500, Train Loss: 0.4394, Val Avg Corr: 0.8383
  >>> New best validation model saved with Avg Corr: 0.8383 <<<
Epoch [3/20], Step 2000, Train Loss: 0.2544, Val Avg Corr: 0.8333
Epoch [3/20], Step 2500, Train Loss: 0.3104, Val Avg Corr: 0.8363
Epoch [3/20], Step 3000, Train Loss: 0.3581, Val Avg Corr: 0.8312
Epoch [3/20], Step 3500, Train Loss: 0.2544, Val Avg Corr: 0.8355
Epoch [3/20], Step 4000, Train Loss: 0.3205, Val Avg Corr: 0.8259
Epoch [3/20], Step 4500, Train Loss: 0.3436, Val Avg Corr: 0.8317
Epoch [3/20], Step 5000, Train Loss: 0.3934, Val Avg Corr: 0.8292
Epoch [3/20], Step 5500, Train Loss: 0.2943, Val Avg Corr: 0.8315
Epoch [3/20], Step 6000, Train Loss: 0.2716, Val Avg Corr: 0.8322
Epoch [3/20], Step 6500, Train Loss: 0.2938, Val Avg Corr: 0.8306
Epoch [3/20], Step 7000, Train Loss: 0.3847, Val Avg Corr: 0.8316
Epoch [3/20], Step 7500, Train Loss: 0.3251, Val Avg Corr: 0.8348
Epoch [3/20], Step 8000, Train Loss: 0.3699, Val Avg Corr: 0.8304
Epoch [3/20], Step 8500, Train Loss: 0.2816, Val Avg Corr: 0.8340
Epoch [3/20], Step 9000, Train Loss: 0.2641, Val Avg Corr: 0.8348
Epoch [3/20], Step 9500, Train Loss: 0.2989, Val Avg Corr: 0.8351
Epoch [3/20], Step 10000, Train Loss: 0.3049, Val Avg Corr: 0.8304
Epoch [3/20], Step 10500, Train Loss: 0.3064, Val Avg Corr: 0.8302
Epoch [3/20], Step 11000, Train Loss: 0.3240, Val Avg Corr: 0.8304
Epoch [3/20], Step 11500, Train Loss: 0.3362, Val Avg Corr: 0.8280
Epoch [3/20], Step 12000, Train Loss: 0.3046, Val Avg Corr: 0.8293
Epoch [3/20], Step 12500, Train Loss: 0.2908, Val Avg Corr: 0.8304
Epoch [3/20], Step 13000, Train Loss: 0.3346, Val Avg Corr: 0.8340
Epoch [3/20], Step 13500, Train Loss: 0.3416, Val Avg Corr: 0.8320
Epoch [3/20], Step 14000, Train Loss: 0.2938, Val Avg Corr: 0.8343
Epoch [3/20], Step 14500, Train Loss: 0.2602, Val Avg Corr: 0.8337
Epoch [3/20], Step 15000, Train Loss: 0.3781, Val Avg Corr: 0.8340
Epoch [3/20], Step 15500, Train Loss: 0.3366, Val Avg Corr: 0.8325
Epoch [3/20], Step 16000, Train Loss: 0.2552, Val Avg Corr: 0.8325
Epoch [3/20], Step 16500, Train Loss: 0.3847, Val Avg Corr: 0.8298
Epoch [3/20], Step 17000, Train Loss: 0.3222, Val Avg Corr: 0.8361
Epoch [3/20], Step 17500, Train Loss: 0.2706, Val Avg Corr: 0.8333
Epoch [3/20], Step 18000, Train Loss: 0.3876, Val Avg Corr: 0.8310
Epoch [3/20], Step 18500, Train Loss: 0.3835, Val Avg Corr: 0.8321
Epoch [3/20], Step 19000, Train Loss: 0.3923, Val Avg Corr: 0.8325
Epoch [3/20], Step 19500, Train Loss: 0.3681, Val Avg Corr: 0.8383
  >>> New best validation model saved with Avg Corr: 0.8383 <<<
Epoch [3/20], Step 20000, Train Loss: 0.3097, Val Avg Corr: 0.8282
Epoch [3/20], Step 20500, Train Loss: 0.3867, Val Avg Corr: 0.8343
Trial change detected: 711 -> 712, resetting states
Epoch [3/20], Step 21000, Train Loss: 0.2293, Val Avg Corr: 0.8348
Epoch [3/20], Step 21500, Train Loss: 0.3547, Val Avg Corr: 0.8342
Epoch [3/20], Step 22000, Train Loss: 0.3195, Val Avg Corr: 0.8299
Epoch [3/20], Step 22500, Train Loss: 0.4072, Val Avg Corr: 0.8257
Epoch [3/20], Step 23000, Train Loss: 0.3463, Val Avg Corr: 0.8290
Epoch [3/20], Step 23500, Train Loss: 0.2728, Val Avg Corr: 0.8264
Epoch [3/20], Step 24000, Train Loss: 0.4116, Val Avg Corr: 0.8274
Epoch [3/20], Step 24500, Train Loss: 0.3414, Val Avg Corr: 0.8319
Epoch [3/20], Step 25000, Train Loss: 0.3447, Val Avg Corr: 0.8252
Epoch [3/20], Step 25500, Train Loss: 0.2660, Val Avg Corr: 0.8241
Epoch [3/20], Step 26000, Train Loss: 0.2345, Val Avg Corr: 0.8283
Epoch [3/20], Step 26500, Train Loss: 0.2598, Val Avg Corr: 0.8337
Epoch [3/20], Step 27000, Train Loss: 0.2277, Val Avg Corr: 0.8279
Epoch [3/20], Step 27500, Train Loss: 0.3353, Val Avg Corr: 0.8339
Epoch [3/20], Step 28000, Train Loss: 0.3518, Val Avg Corr: 0.8356
Epoch [3/20], Step 28500, Train Loss: 0.3011, Val Avg Corr: 0.8295
Epoch [3/20], Step 29000, Train Loss: 0.2759, Val Avg Corr: 0.8353
Epoch [3/20], Step 29500, Train Loss: 0.3175, Val Avg Corr: 0.8395
  >>> New best validation model saved with Avg Corr: 0.8395 <<<
Epoch [3/20], Step 30000, Train Loss: 0.2993, Val Avg Corr: 0.8392
Epoch [3/20], Step 30500, Train Loss: 0.3391, Val Avg Corr: 0.8372
Epoch [3/20], Step 31000, Train Loss: 0.2969, Val Avg Corr: 0.8398
  >>> New best validation model saved with Avg Corr: 0.8398 <<<
Epoch [3/20], Step 31500, Train Loss: 0.2719, Val Avg Corr: 0.8391
Epoch [3/20], Step 32000, Train Loss: 0.2765, Val Avg Corr: 0.8387
Epoch [3/20], Step 32500, Train Loss: 0.3066, Val Avg Corr: 0.8417
  >>> New best validation model saved with Avg Corr: 0.8417 <<<
Epoch [3/20], Step 33000, Train Loss: 0.3121, Val Avg Corr: 0.8410
Epoch [3/20], Step 33500, Train Loss: 0.3532, Val Avg Corr: 0.8348
Epoch [3/20], Step 34000, Train Loss: 0.2468, Val Avg Corr: 0.8457
  >>> New best validation model saved with Avg Corr: 0.8457 <<<
Epoch [3/20], Step 34500, Train Loss: 0.2524, Val Avg Corr: 0.8430
Epoch [3/20], Step 35000, Train Loss: 0.2737, Val Avg Corr: 0.8352
Epoch [3/20], Step 35500, Train Loss: 0.2726, Val Avg Corr: 0.8410
Epoch [3/20], Step 36000, Train Loss: 0.2653, Val Avg Corr: 0.8384
Epoch [3/20], Step 36500, Train Loss: 0.1998, Val Avg Corr: 0.8400
Epoch [3/20], Step 37000, Train Loss: 0.3638, Val Avg Corr: 0.8400
Epoch [3/20], Step 37500, Train Loss: 0.4198, Val Avg Corr: 0.8415
Epoch [3/20], Step 38000, Train Loss: 0.3234, Val Avg Corr: 0.8424
Epoch [3/20], Step 38500, Train Loss: 0.3132, Val Avg Corr: 0.8373
Epoch [3/20], Step 39000, Train Loss: 0.3079, Val Avg Corr: 0.8402
Epoch [3/20], Step 39500, Train Loss: 0.2977, Val Avg Corr: 0.8385
Epoch [3/20], Step 40000, Train Loss: 0.4672, Val Avg Corr: 0.8454
Epoch [3/20], Step 40500, Train Loss: 0.2859, Val Avg Corr: 0.8356
Epoch [3/20], Step 41000, Train Loss: 0.3144, Val Avg Corr: 0.8388
Trial change detected: 1450 -> 1451, resetting states
Epoch [3/20], Step 41500, Train Loss: 0.3467, Val Avg Corr: 0.8412
Epoch [3/20], Step 42000, Train Loss: 0.2349, Val Avg Corr: 0.8429
Epoch [3/20], Step 42500, Train Loss: 0.2990, Val Avg Corr: 0.8390
Epoch [3/20], Step 43000, Train Loss: 0.3293, Val Avg Corr: 0.8420
Epoch [3/20], Step 43500, Train Loss: 0.3636, Val Avg Corr: 0.8428
Epoch [3/20], Step 44000, Train Loss: 0.2949, Val Avg Corr: 0.8409
Epoch [3/20], Step 44500, Train Loss: 0.3533, Val Avg Corr: 0.8372
Epoch [3/20], Step 45000, Train Loss: 0.3513, Val Avg Corr: 0.8397
Epoch [3/20], Step 45500, Train Loss: 0.2437, Val Avg Corr: 0.8485
  >>> New best validation model saved with Avg Corr: 0.8485 <<<
Epoch [3/20], Step 46000, Train Loss: 0.3738, Val Avg Corr: 0.8447
Epoch [3/20], Step 46500, Train Loss: 0.2566, Val Avg Corr: 0.8463
Epoch [3/20], Step 47000, Train Loss: 0.2718, Val Avg Corr: 0.8434
Epoch [3/20], Step 47500, Train Loss: 0.3351, Val Avg Corr: 0.8438
Epoch [3/20], Step 48000, Train Loss: 0.3238, Val Avg Corr: 0.8415
Epoch [3/20], Step 48500, Train Loss: 0.3966, Val Avg Corr: 0.8435
Epoch [3/20], Step 49000, Train Loss: 0.3084, Val Avg Corr: 0.8402
Epoch [3/20], Step 49500, Train Loss: 0.2986, Val Avg Corr: 0.8456
Epoch [3/20], Step 50000, Train Loss: 0.3600, Val Avg Corr: 0.8403
Epoch [3/20], Step 50500, Train Loss: 0.2907, Val Avg Corr: 0.8452
Epoch [3/20], Step 51000, Train Loss: 0.2863, Val Avg Corr: 0.8460
Epoch [3/20], Step 51500, Train Loss: 0.2565, Val Avg Corr: 0.8445
Epoch [3/20], Step 52000, Train Loss: 0.3213, Val Avg Corr: 0.8475
Epoch [3/20], Step 52500, Train Loss: 0.3272, Val Avg Corr: 0.8454
Epoch [3/20], Step 53000, Train Loss: 0.3099, Val Avg Corr: 0.8445
Epoch [3/20], Step 53500, Train Loss: 0.3196, Val Avg Corr: 0.8446
Epoch [3/20], Step 54000, Train Loss: 0.3962, Val Avg Corr: 0.8407
Epoch [3/20], Step 54500, Train Loss: 0.2823, Val Avg Corr: 0.8462
Epoch [3/20], Step 55000, Train Loss: 0.2938, Val Avg Corr: 0.8488
  >>> New best validation model saved with Avg Corr: 0.8488 <<<
Epoch [3/20], Step 55500, Train Loss: 0.3518, Val Avg Corr: 0.8464
Epoch [3/20], Step 56000, Train Loss: 0.3376, Val Avg Corr: 0.8418
Epoch [3/20], Step 56500, Train Loss: 0.3350, Val Avg Corr: 0.8436
Epoch [3/20], Step 57000, Train Loss: 0.3865, Val Avg Corr: 0.8445
Epoch [3/20], Step 57500, Train Loss: 0.2860, Val Avg Corr: 0.8431
Epoch [3/20], Step 58000, Train Loss: 0.2889, Val Avg Corr: 0.8443
Epoch [3/20], Step 58500, Train Loss: 0.3551, Val Avg Corr: 0.8449
Epoch [3/20], Step 59000, Train Loss: 0.3162, Val Avg Corr: 0.8412
Epoch [3/20], Step 59500, Train Loss: 0.2739, Val Avg Corr: 0.8467
Epoch [3/20], Step 60000, Train Loss: 0.3200, Val Avg Corr: 0.8367
Epoch [3/20], Step 60500, Train Loss: 0.3704, Val Avg Corr: 0.8427
Epoch [3/20], Step 61000, Train Loss: 0.2993, Val Avg Corr: 0.8494
  >>> New best validation model saved with Avg Corr: 0.8494 <<<
Epoch [3/20], Step 61500, Train Loss: 0.3519, Val Avg Corr: 0.8448
Trial change detected: 2156 -> 2157, resetting states
Epoch [3/20], Step 62000, Train Loss: 0.3224, Val Avg Corr: 0.8472
Epoch [3/20], Step 62500, Train Loss: 0.2589, Val Avg Corr: 0.8445
Epoch [3/20], Step 63000, Train Loss: 0.3997, Val Avg Corr: 0.8502
  >>> New best validation model saved with Avg Corr: 0.8502 <<<
Epoch [3/20], Step 63500, Train Loss: 0.3215, Val Avg Corr: 0.8480
Epoch [3/20], Step 64000, Train Loss: 0.2952, Val Avg Corr: 0.8467
Epoch [3/20], Step 64500, Train Loss: 0.3079, Val Avg Corr: 0.8389
Epoch [3/20], Step 65000, Train Loss: 0.3125, Val Avg Corr: 0.8443
Epoch [3/20], Step 65500, Train Loss: 0.2867, Val Avg Corr: 0.8493
Epoch [4/20], Step 500, Train Loss: 0.3531, Val Avg Corr: 0.8451
Epoch [4/20], Step 1000, Train Loss: 0.4871, Val Avg Corr: 0.8449
Epoch [4/20], Step 1500, Train Loss: 0.3978, Val Avg Corr: 0.8457
Epoch [4/20], Step 2000, Train Loss: 0.2338, Val Avg Corr: 0.8481
Epoch [4/20], Step 2500, Train Loss: 0.2826, Val Avg Corr: 0.8464
Epoch [4/20], Step 3000, Train Loss: 0.3419, Val Avg Corr: 0.8489
Epoch [4/20], Step 3500, Train Loss: 0.2389, Val Avg Corr: 0.8485
Epoch [4/20], Step 4000, Train Loss: 0.3094, Val Avg Corr: 0.8442
Epoch [4/20], Step 4500, Train Loss: 0.3011, Val Avg Corr: 0.8455
Epoch [4/20], Step 5000, Train Loss: 0.3974, Val Avg Corr: 0.8484
Epoch [4/20], Step 5500, Train Loss: 0.2885, Val Avg Corr: 0.8434
Epoch [4/20], Step 6000, Train Loss: 0.2575, Val Avg Corr: 0.8448
Epoch [4/20], Step 6500, Train Loss: 0.2705, Val Avg Corr: 0.8493
Epoch [4/20], Step 7000, Train Loss: 0.3375, Val Avg Corr: 0.8481
Epoch [4/20], Step 7500, Train Loss: 0.2931, Val Avg Corr: 0.8461
Epoch [4/20], Step 8000, Train Loss: 0.3401, Val Avg Corr: 0.8423
Epoch [4/20], Step 8500, Train Loss: 0.2694, Val Avg Corr: 0.8498
Epoch [4/20], Step 9000, Train Loss: 0.2591, Val Avg Corr: 0.8494
Epoch [4/20], Step 9500, Train Loss: 0.2630, Val Avg Corr: 0.8461
Epoch [4/20], Step 10000, Train Loss: 0.2748, Val Avg Corr: 0.8444
Epoch [4/20], Step 10500, Train Loss: 0.2655, Val Avg Corr: 0.8426
Epoch [4/20], Step 11000, Train Loss: 0.3231, Val Avg Corr: 0.8424
Epoch [4/20], Step 11500, Train Loss: 0.3146, Val Avg Corr: 0.8461
Epoch [4/20], Step 12000, Train Loss: 0.2895, Val Avg Corr: 0.8448
Epoch [4/20], Step 12500, Train Loss: 0.2861, Val Avg Corr: 0.8425
Epoch [4/20], Step 13000, Train Loss: 0.3095, Val Avg Corr: 0.8426
Epoch [4/20], Step 13500, Train Loss: 0.3273, Val Avg Corr: 0.8505
  >>> New best validation model saved with Avg Corr: 0.8505 <<<
Epoch [4/20], Step 14000, Train Loss: 0.2755, Val Avg Corr: 0.8510
  >>> New best validation model saved with Avg Corr: 0.8510 <<<
Epoch [4/20], Step 14500, Train Loss: 0.2462, Val Avg Corr: 0.8498
Epoch [4/20], Step 15000, Train Loss: 0.3608, Val Avg Corr: 0.8482
Epoch [4/20], Step 15500, Train Loss: 0.3228, Val Avg Corr: 0.8468
Epoch [4/20], Step 16000, Train Loss: 0.2377, Val Avg Corr: 0.8451
Epoch [4/20], Step 16500, Train Loss: 0.3666, Val Avg Corr: 0.8428
Epoch [4/20], Step 17000, Train Loss: 0.2911, Val Avg Corr: 0.8481
Epoch [4/20], Step 17500, Train Loss: 0.2618, Val Avg Corr: 0.8453
Epoch [4/20], Step 18000, Train Loss: 0.3659, Val Avg Corr: 0.8466
Epoch [4/20], Step 18500, Train Loss: 0.3488, Val Avg Corr: 0.8463
Epoch [4/20], Step 19000, Train Loss: 0.3732, Val Avg Corr: 0.8436
Epoch [4/20], Step 19500, Train Loss: 0.3269, Val Avg Corr: 0.8427
Epoch [4/20], Step 20000, Train Loss: 0.2852, Val Avg Corr: 0.8430
Epoch [4/20], Step 20500, Train Loss: 0.3532, Val Avg Corr: 0.8472
Trial change detected: 711 -> 712, resetting states
Epoch [4/20], Step 21000, Train Loss: 0.2012, Val Avg Corr: 0.8509
Epoch [4/20], Step 21500, Train Loss: 0.3369, Val Avg Corr: 0.8502
Epoch [4/20], Step 22000, Train Loss: 0.2997, Val Avg Corr: 0.8479
Epoch [4/20], Step 22500, Train Loss: 0.3899, Val Avg Corr: 0.8464
Epoch [4/20], Step 23000, Train Loss: 0.3293, Val Avg Corr: 0.8425
Epoch [4/20], Step 23500, Train Loss: 0.2539, Val Avg Corr: 0.8449
Epoch [4/20], Step 24000, Train Loss: 0.3818, Val Avg Corr: 0.8498
Epoch [4/20], Step 24500, Train Loss: 0.3331, Val Avg Corr: 0.8488
Epoch [4/20], Step 25000, Train Loss: 0.3263, Val Avg Corr: 0.8421
Epoch [4/20], Step 25500, Train Loss: 0.2464, Val Avg Corr: 0.8384
Epoch [4/20], Step 26000, Train Loss: 0.2198, Val Avg Corr: 0.8490
Epoch [4/20], Step 26500, Train Loss: 0.2352, Val Avg Corr: 0.8447
Epoch [4/20], Step 27000, Train Loss: 0.2200, Val Avg Corr: 0.8474
Epoch [4/20], Step 27500, Train Loss: 0.3060, Val Avg Corr: 0.8473
Epoch [4/20], Step 28000, Train Loss: 0.3257, Val Avg Corr: 0.8461
Epoch [4/20], Step 28500, Train Loss: 0.2706, Val Avg Corr: 0.8443
Epoch [4/20], Step 29000, Train Loss: 0.2669, Val Avg Corr: 0.8490
Epoch [4/20], Step 29500, Train Loss: 0.2974, Val Avg Corr: 0.8522
  >>> New best validation model saved with Avg Corr: 0.8522 <<<
Epoch [4/20], Step 30000, Train Loss: 0.2803, Val Avg Corr: 0.8527
  >>> New best validation model saved with Avg Corr: 0.8527 <<<
Epoch [4/20], Step 30500, Train Loss: 0.3067, Val Avg Corr: 0.8518
Epoch [4/20], Step 31000, Train Loss: 0.2834, Val Avg Corr: 0.8487
Epoch [4/20], Step 31500, Train Loss: 0.2672, Val Avg Corr: 0.8478
Epoch [4/20], Step 32000, Train Loss: 0.2546, Val Avg Corr: 0.8537
  >>> New best validation model saved with Avg Corr: 0.8537 <<<
Epoch [4/20], Step 32500, Train Loss: 0.3013, Val Avg Corr: 0.8487
Epoch [4/20], Step 33000, Train Loss: 0.2849, Val Avg Corr: 0.8507
Epoch [4/20], Step 33500, Train Loss: 0.3254, Val Avg Corr: 0.8479
Epoch [4/20], Step 34000, Train Loss: 0.2386, Val Avg Corr: 0.8539
  >>> New best validation model saved with Avg Corr: 0.8539 <<<
Epoch [4/20], Step 34500, Train Loss: 0.2544, Val Avg Corr: 0.8565
  >>> New best validation model saved with Avg Corr: 0.8565 <<<
Epoch [4/20], Step 35000, Train Loss: 0.2724, Val Avg Corr: 0.8499
Epoch [4/20], Step 35500, Train Loss: 0.2616, Val Avg Corr: 0.8515
Epoch [4/20], Step 36000, Train Loss: 0.2562, Val Avg Corr: 0.8523
Epoch [4/20], Step 36500, Train Loss: 0.1884, Val Avg Corr: 0.8481
Epoch [4/20], Step 37000, Train Loss: 0.3418, Val Avg Corr: 0.8529
Epoch [4/20], Step 37500, Train Loss: 0.3813, Val Avg Corr: 0.8491
Epoch [4/20], Step 38000, Train Loss: 0.3103, Val Avg Corr: 0.8543
Epoch [4/20], Step 38500, Train Loss: 0.3085, Val Avg Corr: 0.8455
Epoch [4/20], Step 39000, Train Loss: 0.2913, Val Avg Corr: 0.8510
Epoch [4/20], Step 39500, Train Loss: 0.2774, Val Avg Corr: 0.8528
Epoch [4/20], Step 40000, Train Loss: 0.4419, Val Avg Corr: 0.8539
Epoch [4/20], Step 40500, Train Loss: 0.2669, Val Avg Corr: 0.8505
Epoch [4/20], Step 41000, Train Loss: 0.2992, Val Avg Corr: 0.8484
Trial change detected: 1450 -> 1451, resetting states
Epoch [4/20], Step 41500, Train Loss: 0.3055, Val Avg Corr: 0.8487
Epoch [4/20], Step 42000, Train Loss: 0.2181, Val Avg Corr: 0.8504
Epoch [4/20], Step 42500, Train Loss: 0.2820, Val Avg Corr: 0.8486
Epoch [4/20], Step 43000, Train Loss: 0.3103, Val Avg Corr: 0.8547
Epoch [4/20], Step 43500, Train Loss: 0.3381, Val Avg Corr: 0.8479
Epoch [4/20], Step 44000, Train Loss: 0.2810, Val Avg Corr: 0.8502
Epoch [4/20], Step 44500, Train Loss: 0.3234, Val Avg Corr: 0.8499
Epoch [4/20], Step 45000, Train Loss: 0.3524, Val Avg Corr: 0.8539
Epoch [4/20], Step 45500, Train Loss: 0.2401, Val Avg Corr: 0.8534
Epoch [4/20], Step 46000, Train Loss: 0.3567, Val Avg Corr: 0.8521
Epoch [4/20], Step 46500, Train Loss: 0.2385, Val Avg Corr: 0.8508
Epoch [4/20], Step 47000, Train Loss: 0.2681, Val Avg Corr: 0.8591
  >>> New best validation model saved with Avg Corr: 0.8591 <<<
Epoch [4/20], Step 47500, Train Loss: 0.3134, Val Avg Corr: 0.8532
Epoch [4/20], Step 48000, Train Loss: 0.3006, Val Avg Corr: 0.8513
Epoch [4/20], Step 48500, Train Loss: 0.4117, Val Avg Corr: 0.8572
Epoch [4/20], Step 49000, Train Loss: 0.2755, Val Avg Corr: 0.8538
Epoch [4/20], Step 49500, Train Loss: 0.2973, Val Avg Corr: 0.8538
Epoch [4/20], Step 50000, Train Loss: 0.3478, Val Avg Corr: 0.8619
  >>> New best validation model saved with Avg Corr: 0.8619 <<<
Epoch [4/20], Step 50500, Train Loss: 0.2787, Val Avg Corr: 0.8539
Epoch [4/20], Step 51000, Train Loss: 0.2615, Val Avg Corr: 0.8517
Epoch [4/20], Step 51500, Train Loss: 0.2387, Val Avg Corr: 0.8512
Epoch [4/20], Step 52000, Train Loss: 0.3069, Val Avg Corr: 0.8570
Epoch [4/20], Step 52500, Train Loss: 0.3029, Val Avg Corr: 0.8540
Epoch [4/20], Step 53000, Train Loss: 0.2809, Val Avg Corr: 0.8508
Epoch [4/20], Step 53500, Train Loss: 0.2880, Val Avg Corr: 0.8535
Epoch [4/20], Step 54000, Train Loss: 0.3677, Val Avg Corr: 0.8454
Epoch [4/20], Step 54500, Train Loss: 0.2647, Val Avg Corr: 0.8562
Epoch [4/20], Step 55000, Train Loss: 0.2930, Val Avg Corr: 0.8549
Epoch [4/20], Step 55500, Train Loss: 0.3227, Val Avg Corr: 0.8481
Epoch [4/20], Step 56000, Train Loss: 0.3124, Val Avg Corr: 0.8473
Epoch [4/20], Step 56500, Train Loss: 0.3211, Val Avg Corr: 0.8531
Epoch [4/20], Step 57000, Train Loss: 0.3456, Val Avg Corr: 0.8512
Epoch [4/20], Step 57500, Train Loss: 0.2707, Val Avg Corr: 0.8477
Epoch [4/20], Step 58000, Train Loss: 0.2660, Val Avg Corr: 0.8538
Epoch [4/20], Step 58500, Train Loss: 0.3279, Val Avg Corr: 0.8514
Epoch [4/20], Step 59000, Train Loss: 0.2985, Val Avg Corr: 0.8529
Epoch [4/20], Step 59500, Train Loss: 0.2605, Val Avg Corr: 0.8596
Epoch [4/20], Step 60000, Train Loss: 0.3093, Val Avg Corr: 0.8506
Epoch [4/20], Step 60500, Train Loss: 0.3547, Val Avg Corr: 0.8537
Epoch [4/20], Step 61000, Train Loss: 0.2749, Val Avg Corr: 0.8555
Epoch [4/20], Step 61500, Train Loss: 0.3362, Val Avg Corr: 0.8523
Trial change detected: 2156 -> 2157, resetting states
Epoch [4/20], Step 62000, Train Loss: 0.2964, Val Avg Corr: 0.8528
Epoch [4/20], Step 62500, Train Loss: 0.2629, Val Avg Corr: 0.8572
Epoch [4/20], Step 63000, Train Loss: 0.3764, Val Avg Corr: 0.8598
Epoch [4/20], Step 63500, Train Loss: 0.2802, Val Avg Corr: 0.8498
Epoch [4/20], Step 64000, Train Loss: 0.2750, Val Avg Corr: 0.8559
Epoch [4/20], Step 64500, Train Loss: 0.2827, Val Avg Corr: 0.8548
Epoch [4/20], Step 65000, Train Loss: 0.3041, Val Avg Corr: 0.8588
Epoch [4/20], Step 65500, Train Loss: 0.2563, Val Avg Corr: 0.8575
Epoch [5/20], Step 500, Train Loss: 0.3319, Val Avg Corr: 0.8548
Epoch [5/20], Step 1000, Train Loss: 0.4780, Val Avg Corr: 0.8575
Epoch [5/20], Step 1500, Train Loss: 0.3846, Val Avg Corr: 0.8580
Epoch [5/20], Step 2000, Train Loss: 0.2172, Val Avg Corr: 0.8559
Epoch [5/20], Step 2500, Train Loss: 0.2656, Val Avg Corr: 0.8554
Epoch [5/20], Step 3000, Train Loss: 0.3244, Val Avg Corr: 0.8498
Epoch [5/20], Step 3500, Train Loss: 0.2294, Val Avg Corr: 0.8586
Epoch [5/20], Step 4000, Train Loss: 0.2908, Val Avg Corr: 0.8517
Epoch [5/20], Step 4500, Train Loss: 0.2811, Val Avg Corr: 0.8567
Epoch [5/20], Step 5000, Train Loss: 0.3942, Val Avg Corr: 0.8566
Epoch [5/20], Step 5500, Train Loss: 0.2808, Val Avg Corr: 0.8529
Epoch [5/20], Step 6000, Train Loss: 0.2465, Val Avg Corr: 0.8565
Epoch [5/20], Step 6500, Train Loss: 0.2644, Val Avg Corr: 0.8544
Epoch [5/20], Step 7000, Train Loss: 0.3358, Val Avg Corr: 0.8535
Epoch [5/20], Step 7500, Train Loss: 0.2690, Val Avg Corr: 0.8589
Epoch [5/20], Step 8000, Train Loss: 0.3292, Val Avg Corr: 0.8543
Epoch [5/20], Step 8500, Train Loss: 0.2460, Val Avg Corr: 0.8553
Epoch [5/20], Step 9000, Train Loss: 0.2520, Val Avg Corr: 0.8549
Epoch [5/20], Step 9500, Train Loss: 0.2482, Val Avg Corr: 0.8565
Early stopping triggered after 9500 steps in epoch 5.
  (Patience: 50 eval intervals = 25000 steps)
Loaded best model with validation Corr: 0.8619
Created 1380 trial-aware sequences from 345 trials
  HEBBIAN Results: X=0.8452, Y=0.8170, Avg=0.8311

================================================================================
MCMAZE ABLATION RESULTS SUMMARY
================================================================================
HEBBIAN     : X=0.8366, Y=0.8026, Avg=0.8196
