learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0962	1.0	38	1.0876	0.5364	0.4557	0.4007	0.5364
1.0434	2.0	76	0.9229	0.5894	0.4961	0.4283	0.5894
0.5945	3.0	114	0.3387	0.9205	0.9208	0.9318	0.9205
0.2215	4.0	152	0.2386	0.9272	0.9274	0.9407	0.9272
0.0876	5.0	190	0.1032	0.9735	0.9735	0.9736	0.9735
0.0236	6.0	228	0.3850	0.9404	0.9406	0.9498	0.9404
0.0891	7.0	266	0.0983	0.9801	0.9802	0.9813	0.9801
0.0606	8.0	304	0.3116	0.9470	0.9472	0.9546	0.9470
0.0006	9.0	342	0.3678	0.9470	0.9472	0.9546	0.9470
0.0821	10.0	380	0.0105	1.0	1.0	1.0	1.0
0.0057	11.0	418	0.3436	0.9603	0.9604	0.9647	0.9603
0.1437	12.0	456	0.1034	0.9735	0.9736	0.9741	0.9735
0.0615	13.0	494	0.4131	0.9404	0.9411	0.9498	0.9404
0.0697	14.0	532	0.1664	0.9735	0.9739	0.9759	0.9735
0.0242	15.0	570	0.0595	0.9934	0.9934	0.9935	0.9934
0.0002	16.0	608	0.1706	0.9735	0.9736	0.9755	0.9735
0.0002	17.0	646	0.0598	0.9934	0.9934	0.9935	0.9934
0.0002	18.0	684	0.0776	0.9868	0.9869	0.9874	0.9868
0.0002	19.0	722	0.0805	0.9868	0.9869	0.9874	0.9868
0.0002	20.0	760	0.0826	0.9868	0.9869	0.9874	0.9868

biblo0507/bert2

bert2