CS221-xlm-roberta-base-finetuned-amh

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
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: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4096	1.0	444	0.4063	0.1607	0.5416	0.2213
0.3316	2.0	888	0.3469	0.3841	0.6362	0.3649
0.2866	3.0	1332	0.3261	0.4003	0.6436	0.3902
0.2372	4.0	1776	0.3272	0.4436	0.6579	0.4037
0.2571	5.0	2220	0.3277	0.4953	0.6924	0.4240
0.1821	6.0	2664	0.3426	0.5072	0.7043	0.4274
0.1917	7.0	3108	0.3656	0.4951	0.6977	0.4172
0.1775	8.0	3552	0.3620	0.5292	0.7094	0.4426
0.1457	9.0	3996	0.3958	0.5770	0.7342	0.4443
0.1026	10.0	4440	0.4400	0.5745	0.7357	0.4223
0.0671	11.0	4884	0.4693	0.5869	0.7383	0.4307
0.0587	12.0	5328	0.4951	0.5807	0.7371	0.4291
0.0548	13.0	5772	0.5063	0.6018	0.7557	0.4611
0.0654	14.0	6216	0.5344	0.5991	0.7487	0.4510
0.0613	15.0	6660	0.5403	0.6021	0.7527	0.4459
0.0471	16.0	7104	0.5473	0.6047	0.7490	0.4595
0.0169	17.0	7548	0.5571	0.6056	0.7546	0.4476
0.0178	18.0	7992	0.5618	0.6083	0.7556	0.4645
0.0317	19.0	8436	0.5584	0.6032	0.7511	0.4628
0.0325	20.0	8880	0.5587	0.6064	0.7537	0.4628