learning_rate: 8e-05
train_batch_size: 32
eval_batch_size: 32
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
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Accuracy	F1	Roc Auc
0.1811	0.3436	200	0.1063	0.9570	0.9613	0.9657	0.9590	0.9951
0.0850	0.6873	400	0.0837	0.9717	0.9675	0.9748	0.9695	0.9967
0.0283	1.0309	600	0.1043	0.9644	0.9670	0.9713	0.9656	0.9964
0.0543	1.3746	800	0.0780	0.9765	0.9739	0.9793	0.9752	0.9980
0.0135	1.7182	1000	0.0793	0.9780	0.9752	0.9807	0.9766	0.9978
0.0076	2.0619	1200	0.0851	0.9764	0.9789	0.9814	0.9776	0.9978
0.0066	2.4055	1400	0.0943	0.9789	0.9780	0.9823	0.9784	0.9976
0.0136	2.7491	1600	0.0960	0.9812	0.9766	0.9825	0.9788	0.9981
0.0006	3.0928	1800	0.0882	0.9818	0.9804	0.9844	0.9811	0.9981
0.0001	3.4364	2000	0.0935	0.9810	0.9783	0.9832	0.9796	0.9980
0.0007	3.7801	2200	0.0984	0.9818	0.9785	0.9837	0.9801	0.9980

MinhLe999/global_tf_effnet_l2

global_tf_effnet_l2