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

Collected 108 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_00496               0.917 0.007   0.910   0.923 0.005  [0.917 0.919 0.917 0.907 0.921]
           baseline_00994               0.952 0.006   0.946   0.958 0.005  [0.955 0.949 0.953 0.946 0.958]
           baseline_01986               0.962 0.006   0.956   0.968 0.005  [0.967 0.955 0.962 0.960 0.966]
           baseline_03971               0.899 0.004   0.895   0.903 0.003  [0.901 0.900 0.895 0.896 0.903]
           baseline_07943               0.789 0.003   0.786   0.792 0.002  [0.790 0.791 0.791 0.789 0.785]
           baseline_15887               0.728 0.003   0.725   0.731 0.002  [0.728 0.730 0.726 0.730 0.725]
           cpc_embeddings_00496         0.989 0.005   0.984   0.994 0.004  [0.984 0.994 0.986 0.990 0.990]
           cpc_embeddings_00994         0.995 0.003   0.992   0.998 0.002  [0.992 0.998 0.994 0.995 0.996]
           cpc_embeddings_01986         0.994 0.002   0.993   0.996 0.001  [0.995 0.996 0.993 0.993 0.995]
           cpc_embeddings_03971         0.973 0.001   0.971   0.974 0.001  [0.973 0.974 0.971 0.973 0.973]
           cpc_embeddings_07943         0.860 0.005   0.855   0.865 0.004  [0.857 0.863 0.857 0.865 0.858]
           cpc_embeddings_15887         0.766 0.002   0.764   0.768 0.002  [0.766 0.765 0.764 0.768 0.767]
           mles_embeddings_00496        0.985 0.007   0.978   0.992 0.006  [0.988 0.990 0.980 0.978 0.990]
           mles_embeddings_00994        0.994 0.004   0.989   0.998 0.004  [0.994 0.999 0.993 0.989 0.993]
           mles_embeddings_01986        0.994 0.002   0.992   0.996 0.002  [0.995 0.995 0.992 0.992 0.994]
           mles_embeddings_03971        0.978 0.004   0.974   0.982 0.003  [0.973 0.980 0.978 0.979 0.980]
           mles_embeddings_07943        0.865 0.003   0.862   0.869 0.003  [0.868 0.862 0.866 0.863 0.868]
           mles_embeddings_15887        0.768 0.002   0.766   0.770 0.001  [0.769 0.768 0.768 0.765 0.769]
nn         cpc_finetuning_00496           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_00994           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_01986           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_03971           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_07943           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           cpc_finetuning_15887           nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_00496          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_00994          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_01986          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_03971          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_07943          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           mles_finetuning_15887          nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_00496            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_00994            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_01986            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_03971            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_07943            nan   nan     nan     nan   nan            [nan nan nan nan nan]
           target_scores_15887            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_00496               0.532 0.005   0.527   0.537 0.004  [0.536 0.534 0.526 0.530 0.534]
           baseline_00994               0.557 0.005   0.552   0.562 0.004  [0.561 0.553 0.560 0.552 0.558]
           baseline_01986               0.574 0.006   0.567   0.580 0.005  [0.579 0.568 0.579 0.570 0.571]
           baseline_03971               0.591 0.008   0.583   0.599 0.006  [0.601 0.586 0.587 0.586 0.592]
           baseline_07943               0.606 0.008   0.599   0.614 0.006  [0.613 0.600 0.608 0.600 0.610]
           baseline_15887               0.616 0.004   0.612   0.619 0.003  [0.616 0.613 0.616 0.614 0.620]
           cpc_embeddings_00496         0.564 0.010   0.554   0.573 0.008  [0.567 0.555 0.569 0.572 0.556]
           cpc_embeddings_00994         0.574 0.006   0.568   0.580 0.005  [0.569 0.574 0.577 0.581 0.570]
           cpc_embeddings_01986         0.586 0.009   0.577   0.596 0.007  [0.584 0.586 0.584 0.599 0.580]
           cpc_embeddings_03971         0.596 0.010   0.586   0.605 0.008  [0.593 0.600 0.606 0.593 0.585]
           cpc_embeddings_07943         0.603 0.008   0.595   0.610 0.006  [0.599 0.608 0.609 0.601 0.595]
           cpc_embeddings_15887         0.606 0.005   0.601   0.610 0.004  [0.608 0.610 0.607 0.603 0.601]
           mles_embeddings_00496        0.561 0.011   0.550   0.573 0.009  [0.573 0.563 0.562 0.547 0.562]
           mles_embeddings_00994        0.581 0.008   0.573   0.589 0.006  [0.587 0.575 0.589 0.578 0.576]
           mles_embeddings_01986        0.597 0.009   0.588   0.605 0.007  [0.600 0.592 0.607 0.595 0.590]
           mles_embeddings_03971        0.609 0.005   0.604   0.614 0.004  [0.611 0.611 0.611 0.608 0.602]
           mles_embeddings_07943        0.615 0.008   0.607   0.623 0.006  [0.611 0.612 0.626 0.612 0.614]
           mles_embeddings_15887        0.617 0.008   0.610   0.625 0.006  [0.614 0.617 0.628 0.616 0.612]
nn         cpc_finetuning_00496         0.565 0.004   0.561   0.570 0.003  [0.560 0.569 0.566 0.567 0.565]
           cpc_finetuning_00994         0.583 0.004   0.579   0.587 0.003  [0.580 0.581 0.586 0.583 0.585]
           cpc_finetuning_01986         0.588 0.007   0.582   0.595 0.005  [0.597 0.589 0.586 0.584 0.585]
           cpc_finetuning_03971         0.599 0.003   0.596   0.602 0.003  [0.597 0.600 0.603 0.597 0.599]
           cpc_finetuning_07943         0.614 0.003   0.611   0.617 0.002  [0.611 0.614 0.616 0.616 0.614]
           cpc_finetuning_15887         0.615 0.003   0.612   0.618 0.002  [0.611 0.617 0.616 0.615 0.616]
           mles_finetuning_00496        0.582 0.007   0.575   0.589 0.006  [0.578 0.590 0.584 0.584 0.575]
           mles_finetuning_00994        0.600 0.009   0.592   0.609 0.007  [0.590 0.608 0.605 0.598 0.601]
           mles_finetuning_01986        0.615 0.005   0.610   0.619 0.004  [0.612 0.617 0.620 0.611 0.614]
           mles_finetuning_03971        0.621 0.010   0.611   0.631 0.008  [0.624 0.610 0.627 0.614 0.628]
           mles_finetuning_07943        0.622 0.007   0.615   0.629 0.006  [0.616 0.626 0.627 0.615 0.625]
           mles_finetuning_15887        0.625 0.004   0.621   0.629 0.003  [0.629 0.625 0.624 0.627 0.620]
           target_scores_00496          0.565 0.011   0.554   0.576 0.009  [0.566 0.576 0.565 0.568 0.551]
           target_scores_00994          0.569 0.008   0.561   0.577 0.007  [0.563 0.576 0.569 0.562 0.575]
           target_scores_01986          0.589 0.005   0.584   0.594 0.004  [0.594 0.591 0.587 0.583 0.590]
           target_scores_03971          0.604 0.004   0.600   0.608 0.003  [0.604 0.603 0.599 0.607 0.606]
           target_scores_07943          0.614 0.006   0.607   0.620 0.005  [0.609 0.611 0.612 0.613 0.622]
           target_scores_15887          0.617 0.007   0.610   0.624 0.006  [0.611 0.621 0.621 0.611 0.622]
                                 scores_test                                                             
                                        mean  t_pm t_int_l t_int_h   std                           values
model_name feature_name                                                                                  
lgbm       baseline_00496              0.522 0.017   0.505   0.538 0.013  [0.525 0.543 0.515 0.518 0.508]
           baseline_00994              0.551 0.009   0.541   0.560 0.008  [0.557 0.559 0.549 0.550 0.540]
           baseline_01986              0.573 0.003   0.570   0.576 0.002  [0.573 0.576 0.574 0.569 0.572]
           baseline_03971              0.587 0.008   0.579   0.596 0.007  [0.590 0.580 0.580 0.592 0.593]
           baseline_07943              0.595 0.009   0.586   0.604 0.007  [0.606 0.586 0.596 0.595 0.593]
           baseline_15887              0.603 0.005   0.598   0.609 0.004  [0.605 0.605 0.607 0.605 0.596]
           cpc_embeddings_00496        0.555 0.011   0.543   0.566 0.009  [0.565 0.555 0.559 0.540 0.554]
           cpc_embeddings_00994        0.559 0.008   0.551   0.567 0.006  [0.565 0.552 0.552 0.564 0.562]
           cpc_embeddings_01986        0.568 0.010   0.558   0.578 0.008  [0.580 0.561 0.560 0.569 0.570]
           cpc_embeddings_03971        0.579 0.011   0.568   0.590 0.009  [0.585 0.588 0.565 0.577 0.578]
           cpc_embeddings_07943        0.584 0.007   0.577   0.590 0.005  [0.590 0.577 0.587 0.578 0.586]
           cpc_embeddings_15887        0.589 0.004   0.585   0.593 0.003  [0.591 0.587 0.588 0.593 0.585]
           mles_embeddings_00496       0.547 0.013   0.535   0.560 0.010  [0.549 0.546 0.561 0.532 0.549]
           mles_embeddings_00994       0.568 0.017   0.552   0.585 0.013  [0.578 0.551 0.581 0.558 0.575]
           mles_embeddings_01986       0.580 0.008   0.572   0.589 0.006  [0.585 0.571 0.588 0.580 0.578]
           mles_embeddings_03971       0.592 0.003   0.589   0.595 0.003  [0.595 0.589 0.593 0.589 0.594]
           mles_embeddings_07943       0.598 0.002   0.595   0.600 0.002  [0.600 0.597 0.596 0.598 0.597]
           mles_embeddings_15887       0.600 0.005   0.595   0.605 0.004  [0.601 0.596 0.602 0.605 0.596]
nn         cpc_finetuning_00496        0.560 0.005   0.554   0.565 0.004  [0.556 0.561 0.566 0.556 0.558]
           cpc_finetuning_00994        0.575 0.008   0.567   0.583 0.006  [0.574 0.565 0.580 0.576 0.581]
           cpc_finetuning_01986        0.576 0.006   0.571   0.582 0.005  [0.582 0.571 0.578 0.578 0.572]
           cpc_finetuning_03971        0.594 0.003   0.591   0.596 0.002  [0.594 0.596 0.593 0.590 0.595]
           cpc_finetuning_07943        0.600 0.006   0.594   0.606 0.005  [0.602 0.602 0.604 0.592 0.600]
           cpc_finetuning_15887        0.606 0.005   0.601   0.611 0.004  [0.601 0.605 0.611 0.608 0.607]
           mles_finetuning_00496       0.562 0.010   0.552   0.572 0.008  [0.569 0.568 0.551 0.566 0.556]
           mles_finetuning_00994       0.587 0.013   0.574   0.600 0.010  [0.580 0.601 0.575 0.592 0.589]
           mles_finetuning_01986       0.594 0.008   0.586   0.601 0.006  [0.601 0.599 0.587 0.592 0.590]
           mles_finetuning_03971       0.604 0.005   0.599   0.608 0.004  [0.610 0.603 0.602 0.603 0.600]
           mles_finetuning_07943       0.608 0.004   0.604   0.612 0.003  [0.612 0.606 0.611 0.605 0.606]
           mles_finetuning_15887       0.611 0.004   0.607   0.616 0.003  [0.615 0.609 0.607 0.611 0.615]
           target_scores_00496         0.557 0.007   0.550   0.563 0.005  [0.560 0.562 0.549 0.557 0.555]
           target_scores_00994         0.559 0.006   0.553   0.565 0.005  [0.562 0.564 0.560 0.552 0.555]
           target_scores_01986         0.578 0.006   0.572   0.584 0.005  [0.582 0.575 0.582 0.579 0.571]
           target_scores_03971         0.589 0.009   0.581   0.598 0.007  [0.597 0.586 0.579 0.591 0.593]
           target_scores_07943         0.597 0.006   0.591   0.603 0.005  [0.591 0.598 0.600 0.595 0.603]
           target_scores_15887         0.602 0.006   0.596   0.609 0.005  [0.601 0.600 0.607 0.596 0.608]

------------------------------------------------------------------------------------------------------------------------
End of report.     Current time: 2020-10-01 18:44:05
------------------------------------------------------------------------------------------------------------------------
