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| Training Loss | Epoch | Step | Validation Loss | Hard | Soft | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 178 | 0.1201 | {'precision': 0.6016949152542372, 'recall': 0.7785087719298246, 'f1': 0.678776290630975, 'number': 456} | {'precision': 0.5894736842105263, 'recall': 0.6829268292682927, 'f1': 0.632768361581921, 'number': 82} | 0.6 | 0.7639 | 0.6721 | 0.9508 |
| No log | 2.0 | 356 | 0.1010 | {'precision': 0.6853281853281853, 'recall': 0.7785087719298246, 'f1': 0.728952772073922, 'number': 456} | {'precision': 0.632183908045977, 'recall': 0.6707317073170732, 'f1': 0.6508875739644969, 'number': 82} | 0.6777 | 0.7621 | 0.7174 | 0.9603 |
| 0.1417 | 3.0 | 534 | 0.1026 | {'precision': 0.7030075187969925, 'recall': 0.8201754385964912, 'f1': 0.757085020242915, 'number': 456} | {'precision': 0.65625, 'recall': 0.7682926829268293, 'f1': 0.7078651685393258, 'number': 82} | 0.6959 | 0.8123 | 0.7496 | 0.9598 |
| 0.1417 | 4.0 | 712 | 0.1122 | {'precision': 0.7311411992263056, 'recall': 0.8289473684210527, 'f1': 0.776978417266187, 'number': 456} | {'precision': 0.6464646464646465, 'recall': 0.7804878048780488, 'f1': 0.7071823204419891, 'number': 82} | 0.7175 | 0.8216 | 0.7660 | 0.9616 |
| 0.1417 | 5.0 | 890 | 0.1135 | {'precision': 0.7519685039370079, 'recall': 0.8377192982456141, 'f1': 0.7925311203319502, 'number': 456} | {'precision': 0.6739130434782609, 'recall': 0.7560975609756098, 'f1': 0.7126436781609194, 'number': 82} | 0.74 | 0.8253 | 0.7803 | 0.9647 |