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cs221-deberta-base-multi-label-classifier-finetuned-30-epochs

Name: cs221-deberta-base-multi-label-classifier-finetuned-30-epochs
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cs221-deberta-base-multi-label-classifier-finetuned-30-epochs

This model is a fine-tuned version of Azma-AI/deberta-base-multi-label-classifier on the None dataset. It achieves the following results on the evaluation set:

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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: 30

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4768	1.0	139	0.4340	0.6259	0.7258	0.3105
0.3464	2.0	278	0.3793	0.7232	0.7931	0.4296
0.2699	3.0	417	0.3506	0.7651	0.8253	0.4765
0.1598	4.0	556	0.3764	0.7698	0.8296	0.4874
0.1591	5.0	695	0.3949	0.7614	0.8215	0.4856
0.0994	6.0	834	0.4488	0.7720	0.8272	0.5090
0.0585	7.0	973	0.4811	0.7697	0.8313	0.4729
0.0569	8.0	1112	0.5284	0.7596	0.8218	0.4639
0.0332	9.0	1251	0.5686	0.7726	0.8315	0.4910
0.033	10.0	1390	0.5698	0.7670	0.8270	0.4747
0.0127	11.0	1529	0.6215	0.7709	0.8297	0.4892
0.0136	12.0	1668	0.6239	0.7739	0.8319	0.4910
0.0074	13.0	1807	0.6642	0.7801	0.8357	0.5018
0.0076	14.0	1946	0.6803	0.7752	0.8354	0.4838
0.009	15.0	2085	0.7339	0.7719	0.8302	0.4892
0.0037	16.0	2224	0.6893	0.7780	0.8330	0.4928
0.0075	17.0	2363	0.7387	0.7826	0.8402	0.4982
0.0025	18.0	2502	0.7652	0.7812	0.8388	0.5036
0.0025	19.0	2641	0.7459	0.7758	0.8340	0.4856
0.002	20.0	2780	0.7666	0.7789	0.8355	0.4964
0.0017	21.0	2919	0.7603	0.7782	0.8359	0.4946
0.0022	22.0	3058	0.7743	0.7794	0.8361	0.4964