estudiante_MC318_RLVS

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0561
• Accuracy: 0.9829
• F1: 0.9829
• Precision: 0.9829
• Recall: 0.9829
• Roc Auc: 0.9981

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 30
• eval_batch_size: 30
• 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: linear
• lr_scheduler_warmup_steps: 159
• training_steps: 1590
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
0.4767	1.0145	79	0.4016	0.9011	0.9010	0.9031	0.9011	0.9736
0.3026	2.0289	158	0.2415	0.9465	0.9465	0.9466	0.9465	0.9904
0.2062	4.0082	237	0.1622	0.9626	0.9626	0.9628	0.9626	0.9935
0.1697	5.0226	316	0.1178	0.9679	0.9679	0.9679	0.9679	0.9950
0.1242	7.0019	395	0.1212	0.9759	0.9759	0.9759	0.9759	0.9962
0.0999	8.0164	474	0.0796	0.9706	0.9706	0.9709	0.9706	0.9963
0.0743	9.0308	553	0.0967	0.9759	0.9759	0.9761	0.9759	0.9975
0.0659	11.0101	632	0.0661	0.9840	0.9840	0.9842	0.9840	0.9975
0.0678	12.0245	711	0.0590	0.9840	0.9840	0.9840	0.9840	0.9987
0.0498	14.0038	790	0.0513	0.9840	0.9840	0.9840	0.9840	0.9982
0.0429	15.0182	869	0.0752	0.9813	0.9813	0.9814	0.9813	0.9983

Framework versions

• Transformers 4.46.3
• Pytorch 2.0.1+cu118
• Datasets 3.1.0
• Tokenizers 0.20.3