estudiante_S3D_profesor_MViT_akl_RLVS

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

• Loss: 0.0388
• Accuracy: 0.9882
• F1: 0.9882
• Precision: 0.9882
• Recall: 0.9882
• Roc Auc: 0.9994

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: 40
• eval_batch_size: 40
• 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: 320
• training_steps: 3200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
10.8581	3.0125	160	0.1665	0.9198	0.9196	0.9247	0.9198	0.9854
4.143	7.0125	320	0.0648	0.9759	0.9759	0.9763	0.9759	0.9966
2.3673	11.0125	480	0.0455	0.9866	0.9866	0.9866	0.9866	0.9985
1.9476	15.0125	640	0.0464	0.9866	0.9866	0.9866	0.9866	0.9983
1.2871	19.0125	800	0.0445	0.9893	0.9893	0.9893	0.9893	0.9991
1.4727	23.0125	960	0.0399	0.9893	0.9893	0.9893	0.9893	0.9988
1.5091	27.0125	1120	0.0365	0.9893	0.9893	0.9893	0.9893	0.9991
1.1539	31.0125	1280	0.0470	0.9893	0.9893	0.9893	0.9893	0.9990
1.0804	35.0125	1440	0.0386	0.9893	0.9893	0.9893	0.9893	0.9993
1.1841	39.0125	1600	0.0311	0.9893	0.9893	0.9893	0.9893	0.9992

Framework versions

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