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
0.358	1.0	147	0.3575	0.0786	0.5225	0.3171
0.3248	2.0	294	0.3283	0.1009	0.5356	0.3641
0.3002	3.0	441	0.3139	0.1816	0.5677	0.4338
0.2758	4.0	588	0.2968	0.2087	0.5733	0.4390
0.2252	5.0	735	0.2916	0.3080	0.6210	0.4774
0.208	6.0	882	0.3036	0.3613	0.6439	0.5035
0.1856	7.0	1029	0.3072	0.4059	0.6574	0.5244
0.1731	8.0	1176	0.3202	0.4286	0.6734	0.5035
0.1529	9.0	1323	0.3290	0.4000	0.6585	0.5122
0.1251	10.0	1470	0.3258	0.4290	0.6699	0.5017
0.1321	11.0	1617	0.3239	0.4378	0.6723	0.5035
0.1206	12.0	1764	0.3433	0.4430	0.6831	0.5105
0.1014	13.0	1911	0.3508	0.4323	0.6795	0.5087
0.0975	14.0	2058	0.3548	0.4488	0.6931	0.5087
0.0753	15.0	2205	0.3533	0.4481	0.6880	0.5
0.0809	16.0	2352	0.3656	0.4427	0.6886	0.5105
0.0912	17.0	2499	0.3657	0.4369	0.6831	0.5017
0.0784	18.0	2646	0.3688	0.4435	0.6869	0.5139

Kuongan/xlm-roberta-base-orm-finetuned

xlm-roberta-base-orm-finetuned