xlm-roberta-base-tir-noaug

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: 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
0.3914	1.0	116	0.3936	0.0	0.5	0.2182
0.4009	2.0	232	0.3854	0.0045	0.5009	0.2215
0.3949	3.0	348	0.3737	0.0393	0.5065	0.2524
0.3508	4.0	464	0.3598	0.1551	0.5636	0.2801
0.3268	5.0	580	0.3255	0.2564	0.6012	0.4121
0.3084	6.0	696	0.3513	0.2288	0.5841	0.4055
0.2995	7.0	812	0.3229	0.3084	0.6226	0.4381
0.2783	8.0	928	0.3249	0.3312	0.6376	0.4381
0.2796	9.0	1044	0.3334	0.3356	0.6402	0.4463
0.2732	10.0	1160	0.3341	0.3784	0.6504	0.4625
0.2295	11.0	1276	0.3374	0.3900	0.6521	0.4528
0.2135	12.0	1392	0.3412	0.3878	0.6506	0.4577
0.1955	13.0	1508	0.3439	0.3909	0.6529	0.4593
0.1959	14.0	1624	0.3478	0.4187	0.6631	0.4593
0.1901	15.0	1740	0.3622	0.4026	0.6599	0.4332
0.1818	16.0	1856	0.3585	0.3982	0.6564	0.4463
0.1773	17.0	1972	0.3581	0.3871	0.6484	0.4381
0.1593	18.0	2088	0.3648	0.4097	0.6616	0.4463