learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc	Precision	Recall	F1	F1-macro	F1-micro	F1-weighted
0.4533	0.3850	100	0.3455	0.839	0.93	0.817	0.86	0.838	0.839	0.839	0.839
0.2869	0.7700	200	0.3118	0.879	0.943	0.871	0.88	0.876	0.879	0.879	0.879
0.2335	1.1540	300	0.3963	0.832	0.941	0.881	0.755	0.813	0.831	0.832	0.831
0.2118	1.5390	400	0.6368	0.787	0.897	0.876	0.652	0.748	0.782	0.787	0.783
0.1952	1.9240	500	0.4475	0.839	0.934	0.877	0.775	0.823	0.837	0.839	0.838
0.1649	2.3080	600	0.8635	0.752	0.883	0.882	0.562	0.687	0.741	0.752	0.742
0.1494	2.6930	700	0.7064	0.784	0.908	0.892	0.628	0.737	0.777	0.784	0.778
0.1343	3.0770	800	0.7092	0.803	0.921	0.87	0.698	0.774	0.8	0.803	0.801
0.1037	3.4620	900	0.6272	0.827	0.937	0.887	0.736	0.804	0.825	0.827	0.825
0.1094	3.8470	1000	0.7882	0.803	0.915	0.839	0.734	0.783	0.802	0.803	0.802
0.0938	4.2310	1100	0.6499	0.829	0.936	0.862	0.771	0.814	0.828	0.829	0.829
0.0858	4.6160	1200	0.6244	0.842	0.941	0.881	0.778	0.826	0.84	0.842	0.841
0.0832	5.0	1300	0.5416	0.857	0.951	0.883	0.813	0.846	0.857	0.857	0.857

adity12345/BioBert_Medhhml_v1

BioBert_Medhhml_v1