------------------------------------------------------------------------------------------------------------------------
Vector testing report
Params:
    conf: "conf/embeddings_validation_semi_supervised.hocon"

Collected 180 files with 0 errors

------------------------------------------------------------------------------------------------------------------------
Metric: "accuracy"
                                  scores_train                                                             
                                          mean  t_pm t_int_l t_int_h   std                           values
model_name feature_name                                                                                    
lgbm       baseline_000500               0.998 0.002   0.996   1.000 0.002  [0.998 0.996 0.996 1.000 1.000]
           baseline_001000               1.000 0.001   0.999   1.000 0.000  [1.000 1.000 1.000 1.000 0.999]
           baseline_003000               1.000 0.000   0.999   1.000 0.000  [1.000 1.000 1.000 1.000 0.999]
           baseline_006000               0.999 0.001   0.999   1.000 0.000  [1.000 1.000 0.999 0.999 0.999]
           baseline_012000               0.996 0.001   0.994   0.997 0.001  [0.996 0.997 0.996 0.995 0.994]
           baseline_025000               0.969 0.002   0.968   0.971 0.001  [0.969 0.971 0.968 0.971 0.969]
           baseline_050000               0.903 0.002   0.902   0.905 0.001  [0.903 0.902 0.902 0.905 0.905]
           baseline_100000               0.816 0.002   0.815   0.818 0.001  [0.816 0.818 0.815 0.818 0.817]
           baseline_200000               0.735 0.001   0.734   0.736 0.001  [0.736 0.735 0.734 0.735 0.735]
           baseline_290000               0.699 0.001   0.698   0.700 0.001  [0.701 0.700 0.699 0.698 0.699]
           cpc_embeddings_000500         1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           cpc_embeddings_001000         1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           cpc_embeddings_003000         1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           cpc_embeddings_006000         1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           cpc_embeddings_012000         1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           cpc_embeddings_025000         0.999 0.000   0.999   1.000 0.000  [0.999 1.000 1.000 0.999 0.999]
           cpc_embeddings_050000         0.974 0.001   0.974   0.975 0.001  [0.975 0.974 0.975 0.974 0.974]
           cpc_embeddings_100000         0.874 0.001   0.873   0.875 0.001  [0.875 0.875 0.873 0.873 0.874]
           cpc_embeddings_200000         0.749 0.001   0.749   0.750 0.001  [0.750 0.749 0.749 0.750 0.749]
           cpc_embeddings_290000         0.696 0.001   0.695   0.697 0.001  [0.697 0.697 0.695 0.697 0.696]
           mles_embeddings_000500        1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           mles_embeddings_001000        1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           mles_embeddings_003000        1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           mles_embeddings_006000        1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           mles_embeddings_012000        1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           mles_embeddings_025000        1.000 0.000   1.000   1.000 0.000  [1.000 1.000 1.000 1.000 1.000]
           mles_embeddings_050000        0.995 0.001   0.995   0.996 0.000  [0.995 0.995 0.995 0.995 0.996]
           mles_embeddings_100000        0.925 0.001   0.924   0.926 0.001  [0.926 0.926 0.925 0.925 0.923]
           mles_embeddings_200000        0.800 0.001   0.799   0.801 0.001  [0.801 0.800 0.799 0.800 0.801]
           mles_embeddings_290000        0.741 0.001   0.740   0.742 0.001  [0.742 0.741 0.740 0.741 0.740]
nn         cpc_finetuning_000500           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_001000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_003000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_006000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_012000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_025000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_050000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_100000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_200000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_290000           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_000500          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_001000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_003000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_006000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_012000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_025000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_050000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_100000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_200000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_290000          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_000500            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_001000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_003000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_006000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_012000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_025000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_050000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_100000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_200000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_290000            nan   nan     nan     nan   nan            [nan nan nan nan nan]
                                  scores_valid                                                             
                                          mean  t_pm t_int_l t_int_h   std                           values
model_name feature_name                                                                                    
lgbm       baseline_000500               0.402 0.010   0.392   0.413 0.008  [0.397 0.391 0.404 0.409 0.410]
           baseline_001000               0.431 0.009   0.423   0.440 0.007  [0.422 0.430 0.428 0.437 0.439]
           baseline_003000               0.464 0.004   0.460   0.468 0.003  [0.460 0.466 0.461 0.464 0.468]
           baseline_006000               0.481 0.005   0.476   0.485 0.004  [0.478 0.477 0.481 0.480 0.487]
           baseline_012000               0.496 0.004   0.493   0.500 0.003  [0.492 0.497 0.495 0.497 0.500]
           baseline_025000               0.512 0.004   0.508   0.516 0.003  [0.508 0.511 0.513 0.512 0.516]
           baseline_050000               0.525 0.003   0.522   0.527 0.002  [0.523 0.523 0.525 0.527 0.527]
           baseline_100000               0.536 0.002   0.534   0.538 0.002  [0.535 0.536 0.537 0.536 0.539]
           baseline_200000               0.544 0.002   0.542   0.547 0.002  [0.543 0.542 0.545 0.546 0.546]
           baseline_290000               0.547 0.003   0.544   0.549 0.002  [0.544 0.545 0.548 0.548 0.548]
           cpc_embeddings_000500         0.424 0.010   0.414   0.434 0.008  [0.416 0.419 0.418 0.431 0.434]
           cpc_embeddings_001000         0.447 0.007   0.440   0.454 0.006  [0.442 0.451 0.439 0.451 0.451]
           cpc_embeddings_003000         0.470 0.002   0.468   0.472 0.002  [0.467 0.471 0.471 0.471 0.470]
           cpc_embeddings_006000         0.482 0.002   0.480   0.484 0.002  [0.481 0.481 0.482 0.482 0.485]
           cpc_embeddings_012000         0.491 0.002   0.489   0.493 0.001  [0.489 0.490 0.492 0.491 0.492]
           cpc_embeddings_025000         0.498 0.004   0.494   0.502 0.003  [0.495 0.497 0.502 0.496 0.500]
           cpc_embeddings_050000         0.506 0.004   0.502   0.510 0.003  [0.503 0.504 0.510 0.503 0.509]
           cpc_embeddings_100000         0.514 0.004   0.510   0.518 0.003  [0.511 0.511 0.518 0.513 0.517]
           cpc_embeddings_200000         0.521 0.005   0.516   0.525 0.004  [0.517 0.519 0.525 0.518 0.525]
           cpc_embeddings_290000         0.525 0.003   0.522   0.528 0.002  [0.523 0.525 0.525 0.523 0.528]
           mles_embeddings_000500        0.453 0.008   0.445   0.461 0.007  [0.444 0.449 0.453 0.459 0.460]
           mles_embeddings_001000        0.473 0.009   0.465   0.482 0.007  [0.467 0.480 0.465 0.476 0.480]
           mles_embeddings_003000        0.494 0.001   0.493   0.496 0.001  [0.494 0.494 0.493 0.496 0.495]
           mles_embeddings_006000        0.505 0.003   0.502   0.507 0.002  [0.503 0.503 0.504 0.505 0.508]
           mles_embeddings_012000        0.512 0.002   0.510   0.513 0.001  [0.510 0.511 0.512 0.512 0.513]
           mles_embeddings_025000        0.518 0.002   0.516   0.520 0.002  [0.518 0.516 0.519 0.517 0.520]
           mles_embeddings_050000        0.524 0.001   0.523   0.526 0.001  [0.524 0.524 0.525 0.523 0.525]
           mles_embeddings_100000        0.531 0.002   0.529   0.533 0.002  [0.529 0.529 0.532 0.530 0.534]
           mles_embeddings_200000        0.538 0.002   0.536   0.541 0.002  [0.538 0.535 0.540 0.538 0.540]
           mles_embeddings_290000        0.542 0.002   0.540   0.544 0.002  [0.542 0.540 0.544 0.542 0.544]
nn         cpc_finetuning_000500         0.430 0.008   0.421   0.438 0.007  [0.432 0.429 0.429 0.439 0.420]
           cpc_finetuning_001000         0.456 0.006   0.450   0.461 0.005  [0.460 0.450 0.453 0.454 0.461]
           cpc_finetuning_003000         0.492 0.004   0.488   0.496 0.003  [0.488 0.490 0.495 0.494 0.491]
           cpc_finetuning_006000         0.501 0.004   0.497   0.504 0.003  [0.498 0.499 0.504 0.499 0.503]
           cpc_finetuning_012000         0.513 0.002   0.511   0.515 0.002  [0.512 0.511 0.513 0.512 0.516]
           cpc_finetuning_025000         0.524 0.003   0.521   0.527 0.003  [0.521 0.522 0.527 0.525 0.526]
           cpc_finetuning_050000         0.533 0.002   0.531   0.535 0.001  [0.532 0.533 0.532 0.533 0.536]
           cpc_finetuning_100000         0.541 0.002   0.539   0.542 0.001  [0.540 0.539 0.541 0.540 0.543]
           cpc_finetuning_200000         0.547 0.001   0.546   0.548 0.001  [0.547 0.546 0.546 0.546 0.548]
           cpc_finetuning_290000         0.551 0.002   0.548   0.553 0.002  [0.552 0.550 0.552 0.548 0.550]
           mles_finetuning_000500        0.432 0.012   0.420   0.444 0.010  [0.449 0.427 0.427 0.429 0.428]
           mles_finetuning_001000        0.462 0.005   0.457   0.467 0.004  [0.469 0.459 0.460 0.460 0.460]
           mles_finetuning_003000        0.494 0.002   0.492   0.495 0.001  [0.492 0.494 0.495 0.492 0.494]
           mles_finetuning_006000        0.506 0.002   0.505   0.508 0.001  [0.505 0.505 0.508 0.507 0.507]
           mles_finetuning_012000        0.520 0.002   0.517   0.522 0.002  [0.521 0.517 0.522 0.519 0.520]
           mles_finetuning_025000        0.532 0.002   0.531   0.534 0.001  [0.532 0.531 0.533 0.531 0.534]
           mles_finetuning_050000        0.540 0.002   0.538   0.542 0.002  [0.539 0.539 0.543 0.539 0.540]
           mles_finetuning_100000        0.546 0.001   0.545   0.546 0.000  [0.546 0.545 0.546 0.546 0.546]
           mles_finetuning_200000        0.551 0.002   0.550   0.553 0.001  [0.553 0.551 0.552 0.550 0.551]
           mles_finetuning_290000        0.555 0.002   0.552   0.557 0.002  [0.556 0.554 0.555 0.552 0.557]
           target_scores_000500          0.412 0.006   0.406   0.417 0.005  [0.417 0.408 0.407 0.410 0.416]
           target_scores_001000          0.439 0.003   0.436   0.441 0.002  [0.438 0.441 0.437 0.436 0.440]
           target_scores_003000          0.471 0.013   0.458   0.484 0.010  [0.480 0.477 0.479 0.460 0.460]
           target_scores_006000          0.490 0.005   0.485   0.496 0.004  [0.492 0.497 0.486 0.486 0.490]
           target_scores_012000          0.504 0.003   0.501   0.508 0.003  [0.501 0.507 0.502 0.506 0.505]
           target_scores_025000          0.512 0.002   0.510   0.515 0.002  [0.514 0.514 0.513 0.510 0.511]
           target_scores_050000          0.524 0.001   0.523   0.525 0.001  [0.524 0.524 0.522 0.523 0.525]
           target_scores_100000          0.533 0.001   0.532   0.534 0.001  [0.533 0.532 0.534 0.533 0.533]
           target_scores_200000          0.540 0.002   0.538   0.542 0.002  [0.537 0.541 0.540 0.542 0.540]
           target_scores_290000          0.543 0.002   0.542   0.545 0.001  [0.545 0.542 0.545 0.542 0.543]
                                  scores_test                                                             
                                         mean  t_pm t_int_l t_int_h   std                           values
model_name feature_name                                                                                   
lgbm       baseline_000500              0.402 0.010   0.392   0.411 0.008  [0.394 0.393 0.405 0.411 0.405]
           baseline_001000              0.431 0.006   0.424   0.437 0.005  [0.424 0.430 0.428 0.433 0.438]
           baseline_003000              0.463 0.003   0.460   0.465 0.002  [0.464 0.464 0.462 0.460 0.465]
           baseline_006000              0.481 0.004   0.476   0.485 0.003  [0.479 0.478 0.480 0.479 0.487]
           baseline_012000              0.497 0.003   0.494   0.500 0.002  [0.496 0.494 0.496 0.497 0.501]
           baseline_025000              0.513 0.002   0.510   0.515 0.002  [0.512 0.514 0.512 0.510 0.515]
           baseline_050000              0.526 0.002   0.525   0.528 0.001  [0.528 0.525 0.525 0.526 0.527]
           baseline_100000              0.535 0.001   0.534   0.537 0.001  [0.534 0.535 0.535 0.535 0.537]
           baseline_200000              0.544 0.002   0.542   0.546 0.002  [0.543 0.543 0.547 0.545 0.545]
           baseline_290000              0.547 0.002   0.546   0.549 0.001  [0.547 0.546 0.548 0.545 0.548]
           cpc_embeddings_000500        0.423 0.010   0.413   0.433 0.008  [0.418 0.415 0.418 0.428 0.434]
           cpc_embeddings_001000        0.447 0.007   0.440   0.455 0.006  [0.443 0.452 0.440 0.447 0.454]
           cpc_embeddings_003000        0.472 0.002   0.469   0.474 0.002  [0.469 0.474 0.472 0.472 0.472]
           cpc_embeddings_006000        0.482 0.003   0.479   0.485 0.002  [0.483 0.480 0.482 0.480 0.485]
           cpc_embeddings_012000        0.492 0.004   0.488   0.496 0.003  [0.492 0.495 0.492 0.488 0.495]
           cpc_embeddings_025000        0.499 0.004   0.495   0.503 0.003  [0.496 0.501 0.500 0.495 0.502]
           cpc_embeddings_050000        0.507 0.001   0.506   0.508 0.001  [0.506 0.508 0.507 0.506 0.508]
           cpc_embeddings_100000        0.514 0.003   0.512   0.517 0.002  [0.514 0.516 0.515 0.511 0.516]
           cpc_embeddings_200000        0.522 0.001   0.521   0.523 0.001  [0.521 0.522 0.523 0.521 0.522]
           cpc_embeddings_290000        0.525 0.001   0.523   0.526 0.001  [0.526 0.525 0.523 0.524 0.524]
           mles_embeddings_000500       0.453 0.009   0.444   0.463 0.008  [0.444 0.446 0.457 0.460 0.459]
           mles_embeddings_001000       0.473 0.006   0.467   0.479 0.005  [0.468 0.480 0.470 0.472 0.477]
           mles_embeddings_003000       0.494 0.000   0.494   0.495 0.000  [0.494 0.494 0.494 0.494 0.494]
           mles_embeddings_006000       0.505 0.001   0.504   0.505 0.001  [0.505 0.505 0.505 0.504 0.504]
           mles_embeddings_012000       0.511 0.003   0.508   0.514 0.002  [0.511 0.514 0.508 0.510 0.510]
           mles_embeddings_025000       0.516 0.002   0.514   0.518 0.002  [0.518 0.517 0.514 0.515 0.517]
           mles_embeddings_050000       0.523 0.001   0.522   0.525 0.001  [0.524 0.523 0.523 0.523 0.525]
           mles_embeddings_100000       0.530 0.002   0.529   0.532 0.001  [0.530 0.530 0.531 0.529 0.533]
           mles_embeddings_200000       0.537 0.002   0.535   0.539 0.002  [0.538 0.537 0.534 0.537 0.538]
           mles_embeddings_290000       0.539 0.002   0.537   0.541 0.002  [0.540 0.539 0.540 0.537 0.541]
nn         cpc_finetuning_000500        0.432 0.009   0.423   0.441 0.007  [0.435 0.430 0.434 0.440 0.420]
           cpc_finetuning_001000        0.458 0.005   0.453   0.464 0.004  [0.461 0.454 0.457 0.455 0.464]
           cpc_finetuning_003000        0.492 0.003   0.489   0.495 0.002  [0.490 0.491 0.495 0.494 0.490]
           cpc_finetuning_006000        0.501 0.004   0.497   0.505 0.003  [0.502 0.497 0.501 0.498 0.505]
           cpc_finetuning_012000        0.512 0.002   0.510   0.514 0.001  [0.512 0.510 0.511 0.513 0.514]
           cpc_finetuning_025000        0.522 0.002   0.520   0.524 0.002  [0.520 0.521 0.524 0.522 0.523]
           cpc_finetuning_050000        0.532 0.001   0.531   0.533 0.001  [0.532 0.533 0.532 0.531 0.531]
           cpc_finetuning_100000        0.539 0.001   0.538   0.540 0.001  [0.540 0.539 0.539 0.539 0.538]
           cpc_finetuning_200000        0.545 0.001   0.544   0.546 0.001  [0.545 0.545 0.544 0.546 0.546]
           cpc_finetuning_290000        0.549 0.001   0.547   0.550 0.001  [0.550 0.548 0.549 0.547 0.548]
           mles_finetuning_000500       0.433 0.012   0.421   0.445 0.009  [0.450 0.427 0.429 0.428 0.431]
           mles_finetuning_001000       0.463 0.002   0.461   0.465 0.002  [0.465 0.461 0.462 0.464 0.463]
           mles_finetuning_003000       0.493 0.004   0.489   0.496 0.003  [0.488 0.494 0.495 0.493 0.494]
           mles_finetuning_006000       0.505 0.002   0.504   0.507 0.001  [0.503 0.506 0.506 0.506 0.505]
           mles_finetuning_012000       0.517 0.001   0.516   0.518 0.001  [0.516 0.517 0.517 0.517 0.519]
           mles_finetuning_025000       0.530 0.002   0.529   0.532 0.001  [0.532 0.530 0.529 0.531 0.530]
           mles_finetuning_050000       0.539 0.001   0.538   0.540 0.001  [0.539 0.540 0.540 0.539 0.538]
           mles_finetuning_100000       0.544 0.001   0.544   0.545 0.000  [0.544 0.544 0.543 0.545 0.544]
           mles_finetuning_200000       0.549 0.002   0.547   0.551 0.002  [0.549 0.548 0.547 0.549 0.552]
           mles_finetuning_290000       0.552 0.001   0.552   0.553 0.001  [0.552 0.553 0.553 0.552 0.553]
           target_scores_000500         0.415 0.005   0.410   0.420 0.004  [0.418 0.410 0.415 0.411 0.420]
           target_scores_001000         0.440 0.002   0.438   0.443 0.002  [0.439 0.439 0.441 0.440 0.443]
           target_scores_003000         0.473 0.011   0.463   0.484 0.008  [0.481 0.478 0.480 0.464 0.464]
           target_scores_006000         0.491 0.005   0.486   0.496 0.004  [0.487 0.497 0.492 0.487 0.493]
           target_scores_012000         0.503 0.004   0.499   0.508 0.004  [0.501 0.508 0.499 0.505 0.504]
           target_scores_025000         0.514 0.003   0.511   0.517 0.002  [0.516 0.517 0.511 0.513 0.512]
           target_scores_050000         0.524 0.003   0.521   0.527 0.003  [0.524 0.525 0.520 0.524 0.527]
           target_scores_100000         0.533 0.001   0.531   0.534 0.001  [0.532 0.531 0.534 0.533 0.533]
           target_scores_200000         0.538 0.002   0.536   0.541 0.002  [0.537 0.541 0.537 0.539 0.538]
           target_scores_290000         0.542 0.001   0.541   0.543 0.001  [0.541 0.542 0.541 0.543 0.542]

------------------------------------------------------------------------------------------------------------------------
End of report.     Current time: 2020-10-01 17:56:10
------------------------------------------------------------------------------------------------------------------------
