estudiante_Swin3D_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: 0.0952
• Accuracy: 0.9803
• F1: 0.9803
• Precision: 0.9804
• Recall: 0.9803
• Roc Auc: 0.9983

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
0.4009	1.0214	280	0.0800	0.9817	0.9817	0.9818	0.9817	0.9915
0.2826	3.0143	560	0.0801	0.9764	0.9764	0.9766	0.9764	0.9952
0.115	5.0071	840	0.0997	0.9738	0.9738	0.9747	0.9738	0.9960
0.0979	6.0286	1120	0.0904	0.9791	0.9791	0.9791	0.9791	0.9945
0.0735	8.0214	1400	0.0633	0.9843	0.9843	0.9843	0.9843	0.9966
0.0856	10.0143	1680	0.0721	0.9843	0.9843	0.9843	0.9843	0.9966
0.0532	12.0071	1960	0.0573	0.9869	0.9869	0.9869	0.9869	0.9979
0.103	13.0286	2240	0.0566	0.9895	0.9895	0.9895	0.9895	0.9987
0.0345	15.0214	2520	0.1021	0.9817	0.9817	0.9818	0.9817	0.9990
0.0579	17.0143	2800	0.0632	0.9869	0.9869	0.9869	0.9869	0.9987
0.035	19.0071	3080	0.1293	0.9791	0.9791	0.9793	0.9791	0.9949
0.0535	20.0286	3360	0.0768	0.9791	0.9791	0.9795	0.9791	0.9986
0.0802	22.0214	3640	0.0601	0.9869	0.9869	0.9869	0.9869	0.9986

Framework versions

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