UIT-roberta-large-finetuned

This model is a fine-tuned version of FacebookAI/roberta-large 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: 16
eval_batch_size: 16
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
0.4959	1.0	139	0.4214	0.4807	0.6598	0.3375
0.3785	2.0	278	0.3560	0.7080	0.7697	0.4314
0.2713	3.0	417	0.3301	0.7451	0.8055	0.4910
0.1539	4.0	556	0.3920	0.7364	0.7963	0.4603
0.1307	5.0	695	0.4197	0.7320	0.7892	0.4819
0.0868	6.0	834	0.4604	0.7280	0.7891	0.4819
0.0449	7.0	973	0.4778	0.7450	0.8063	0.4838
0.064	8.0	1112	0.4934	0.7654	0.8248	0.4964
0.0379	9.0	1251	0.5534	0.7490	0.8148	0.4801
0.0141	10.0	1390	0.5641	0.7397	0.8048	0.4801
0.0143	11.0	1529	0.5763	0.7517	0.8166	0.4928
0.0067	12.0	1668	0.5987	0.7448	0.8035	0.5036
0.0045	13.0	1807	0.5933	0.7576	0.8155	0.5162
0.004	14.0	1946	0.6058	0.7558	0.8132	0.5054
0.0025	15.0	2085	0.6091	0.7531	0.8138	0.5018
0.0024	16.0	2224	0.6189	0.7540	0.8124	0.5054
0.0025	17.0	2363	0.6259	0.7532	0.8122	0.5054
0.0027	18.0	2502	0.6255	0.7568	0.8138	0.5108
0.0022	19.0	2641	0.6267	0.7553	0.8130	0.5072
0.0022	20.0	2780	0.6263	0.7549	0.8127	0.5072