learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
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: 10

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.1446	1.0	2129	0.1396	0.2823	0.5866	0.4469
0.1155	2.0	4258	0.1132	0.5384	0.7209	0.5225
0.1021	3.0	6387	0.1065	0.5995	0.7767	0.5325
0.0899	4.0	8516	0.1030	0.6104	0.7780	0.5484
0.0764	5.0	10645	0.1006	0.6234	0.7881	0.5542
0.0684	6.0	12774	0.1017	0.6365	0.8033	0.5579
0.0605	7.0	14903	0.1043	0.6279	0.7924	0.5597
0.0549	8.0	17032	0.1076	0.6317	0.8013	0.5534
0.0515	9.0	19161	0.1089	0.6322	0.8026	0.5531
0.0486	10.0	21290	0.1094	0.6286	0.8000	0.5521

tranglam/roberta-finetuned-bca-v2

roberta-finetuned-bca-v2