learning_rate: 0.0001
train_batch_size: 24
eval_batch_size: 24
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 4

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Accuracy	F1	Roc Auc
0.3639	0.2577	200	12.4134	0.8978	0.9088	0.9128	0.8996	0.9862
0.2433	0.5155	400	1.5055	0.7737	0.6830	0.6291	0.6382	0.9657
0.2974	0.7732	600	0.1301	0.9570	0.9435	0.9585	0.9491	0.9944
0.0867	1.0309	800	0.1688	0.9438	0.9530	0.9552	0.9472	0.9959
0.0392	1.2887	1000	0.2777	0.9549	0.9195	0.9448	0.9313	0.9970
0.2445	1.5464	1200	0.1142	0.9770	0.9689	0.9772	0.9726	0.9971
0.1727	1.8041	1400	0.2502	0.9683	0.9680	0.9737	0.9682	0.9964
0.1100	2.0619	1600	0.1452	0.9652	0.9707	0.9730	0.9676	0.9976
0.0381	2.3196	1800	0.1217	0.9779	0.9708	0.9788	0.9741	0.9974
0.0441	2.5773	2000	0.1124	0.9762	0.9764	0.9804	0.9763	0.9979
0.0792	2.8351	2200	0.1406	0.9821	0.9772	0.9832	0.9795	0.9983
0.0010	3.0928	2400	0.0857	0.9806	0.9794	0.9834	0.9800	0.9986
0.0003	3.3505	2600	0.1904	0.9821	0.9776	0.9832	0.9797	0.9980
0.0011	3.6082	2800	0.0997	0.9815	0.9790	0.9837	0.9803	0.9984
0.0053	3.8660	3000	0.1172	0.9797	0.9769	0.9821	0.9783	0.9980

MinhLe999/global_mbv4_hybrid_large

global_mbv4_hybrid_large