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metadata
library_name: transformers
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: estudiante_Swin3D_RLVS
    results: []

estudiante_Swin3D_RLVS

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

  • Loss: 0.0766
  • Accuracy: 0.9816
  • F1: 0.9816
  • Precision: 0.9817
  • Recall: 0.9816
  • Roc Auc: 0.9988

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: 15
  • eval_batch_size: 15
  • 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: 318
  • training_steps: 3180
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall Roc Auc
0.2317 1.0160 159 0.1561 0.9412 0.9410 0.9453 0.9412 0.9878
0.1354 2.0321 318 0.0908 0.9652 0.9652 0.9654 0.9652 0.9939
0.0698 4.0142 477 0.1050 0.9679 0.9679 0.9688 0.9679 0.9952
0.0767 5.0302 636 0.0930 0.9759 0.9759 0.9761 0.9759 0.9972
0.0576 7.0123 795 0.0916 0.9786 0.9786 0.9787 0.9786 0.9975
0.0514 8.0283 954 0.0840 0.9813 0.9813 0.9814 0.9813 0.9985
0.0481 10.0104 1113 0.1026 0.9733 0.9733 0.9733 0.9733 0.9980
0.0257 11.0264 1272 0.1148 0.9813 0.9813 0.9814 0.9813 0.9966
0.03 13.0085 1431 0.1170 0.9759 0.9759 0.9761 0.9759 0.9981
0.0302 14.0245 1590 0.1537 0.9733 0.9733 0.9735 0.9733 0.9978
0.0414 16.0066 1749 0.1367 0.9786 0.9786 0.9787 0.9786 0.9981

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.0.1+cu118
  • Datasets 3.1.0
  • Tokenizers 0.20.3