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: 2
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc	Precision	Recall	F1	F1-macro	F1-micro	F1-weighted
0.5271	0.1935	1000	1.0367	0.595	0.57	0.567	0.751	0.646	0.587	0.595	0.586
0.439	0.3870	2000	1.2336	0.594	0.576	0.558	0.832	0.668	0.573	0.594	0.571
0.4166	0.5805	3000	1.3620	0.606	0.57	0.569	0.814	0.67	0.591	0.606	0.59
0.3997	0.7740	4000	1.3161	0.61	0.59	0.575	0.787	0.664	0.599	0.61	0.598
0.391	0.9675	5000	1.3359	0.613	0.596	0.573	0.833	0.679	0.596	0.613	0.595
0.3618	1.1610	6000	1.4006	0.617	0.603	0.578	0.817	0.677	0.603	0.617	0.602
0.3564	1.3545	7000	1.3645	0.619	0.612	0.584	0.782	0.669	0.611	0.619	0.61
0.352	1.5480	8000	1.4672	0.617	0.601	0.582	0.785	0.668	0.608	0.617	0.606
0.3465	1.7415	9000	1.4327	0.62	0.609	0.586	0.771	0.666	0.613	0.62	0.612
0.3413	1.9350	10000	1.4440	0.62	0.608	0.581	0.814	0.678	0.608	0.62	0.607

adity12345/Roberta_combo_1.6lakh

Roberta_combo_1.6lakh