estudiante_Swin3D_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: 0.0711
• Accuracy: 0.9829
• F1: 0.9829
• Precision: 0.9829
• Recall: 0.9829
• Roc Auc: 0.9977

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: 10
• eval_batch_size: 10
• 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: 560
• training_steps: 5600
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
6.829	1.0214	280	0.0851	0.9791	0.9791	0.9791	0.9791	0.9920
3.7322	3.0143	560	0.0727	0.9817	0.9817	0.9817	0.9817	0.9935
1.8264	5.0071	840	0.1005	0.9764	0.9764	0.9771	0.9764	0.9906
1.3973	6.0286	1120	0.1179	0.9817	0.9817	0.9817	0.9817	0.9970
1.4977	8.0214	1400	0.0639	0.9843	0.9843	0.9843	0.9843	0.9981
1.8736	10.0143	1680	0.0933	0.9791	0.9791	0.9793	0.9791	0.9838

Framework versions

• Transformers 4.46.2
• Pytorch 2.0.1+cu118
• Datasets 3.1.0
• Tokenizers 0.20.3