estudiante_S3D_profesor_MViT_kl_RLVS

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

• Loss: 0.0504
• Accuracy: 0.9868
• F1: 0.9868
• Precision: 0.9869
• Recall: 0.9868
• Roc Auc: 0.9987

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
0.6173	3.0125	160	0.2047	0.9171	0.9167	0.9261	0.9171	0.9840
0.2463	7.0125	320	0.0819	0.9679	0.9679	0.9688	0.9679	0.9949
0.1257	11.0125	480	0.0515	0.9786	0.9786	0.9786	0.9786	0.9981
0.1012	15.0125	640	0.0533	0.9840	0.9840	0.9840	0.9840	0.9983
0.0633	19.0125	800	0.0562	0.9893	0.9893	0.9893	0.9893	0.9986
0.0721	23.0125	960	0.0503	0.9866	0.9866	0.9866	0.9866	0.9981
0.0721	27.0125	1120	0.0482	0.9759	0.9759	0.9759	0.9759	0.9984
0.056	31.0125	1280	0.0599	0.9866	0.9866	0.9866	0.9866	0.9986
0.0565	35.0125	1440	0.0515	0.9866	0.9866	0.9866	0.9866	0.9985
0.0613	39.0125	1600	0.0436	0.9840	0.9840	0.9840	0.9840	0.9979

Framework versions

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