learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.5359	1.0	76	0.4176	0.0	0.5	0.2
0.4189	2.0	152	0.3690	0.0	0.5	0.2
0.2912	3.0	228	0.2125	0.6016	0.7496	0.61
0.1983	4.0	304	0.1391	0.8669	0.8883	0.84
0.1411	5.0	380	0.1134	0.8862	0.9178	0.85
0.1327	6.0	456	0.0949	0.9084	0.9363	0.89
0.113	7.0	532	0.0820	0.9119	0.9367	0.89
0.0842	8.0	608	0.0839	0.9222	0.9410	0.89
0.0736	9.0	684	0.0855	0.9116	0.9378	0.88
0.0634	10.0	760	0.0701	0.9296	0.9485	0.89
0.0535	11.0	836	0.0789	0.9166	0.9456	0.85
0.0483	12.0	912	0.0853	0.9131	0.9485	0.85
0.0443	13.0	988	0.0808	0.9224	0.9549	0.87
0.0442	14.0	1064	0.0820	0.9229	0.9510	0.87

Kuongan/xlm-roberta-base-mar-noaug

xlm-roberta-base-mar-noaug