estudiante_S3D_VIOPERU

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

• Loss: 0.6343
• Accuracy: 0.6875
• F1: 0.6537
• Precision: 0.8077
• Recall: 0.6875
• Roc Auc: 0.7296

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: 75
• eval_batch_size: 75
• 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: 18
• training_steps: 180
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
0.7424	2.0056	9	0.7396	0.5	0.3333	0.25	0.5	0.4490
0.6674	4.0111	18	0.7129	0.5179	0.3718	0.7545	0.5179	0.5242
0.6027	6.0167	27	0.7228	0.6071	0.5354	0.78	0.6071	0.5931
0.5256	8.0222	36	0.6547	0.6607	0.6166	0.7979	0.6607	0.6671
0.4766	11.0056	45	0.6149	0.6786	0.6415	0.8043	0.6786	0.7181
0.4165	13.0111	54	0.6709	0.6786	0.6415	0.8043	0.6786	0.7487
0.4021	15.0167	63	0.6160	0.6786	0.6415	0.8043	0.6786	0.7730
0.3406	17.0222	72	0.5971	0.6429	0.6111	0.7121	0.6429	0.7972
0.316	20.0056	81	0.6109	0.6607	0.6345	0.7254	0.6607	0.8176
0.2818	22.0111	90	0.5283	0.6607	0.6345	0.7254	0.6607	0.8393

Framework versions

• Transformers 4.46.1
• Pytorch 2.0.1+cu118
• Datasets 3.1.0
• Tokenizers 0.20.1