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metadata
library_name: transformers
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: profesor_MViT_N_RWF2000
    results: []

profesor_MViT_N_RWF2000

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

  • Loss: 0.2366
  • Accuracy: 0.92
  • F1: 0.9200
  • Precision: 0.9205
  • Recall: 0.92
  • Roc Auc: 0.9722

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: 20
  • eval_batch_size: 20
  • 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: 240
  • training_steps: 2400
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall Roc Auc
0.5576 2.0333 240 0.4177 0.89 0.8900 0.8902 0.89 0.9554
0.2715 5.0333 480 0.2499 0.9225 0.9225 0.9234 0.9225 0.9768
0.1905 8.0333 720 0.2218 0.925 0.9250 0.9261 0.925 0.9799
0.1934 11.0333 960 0.2321 0.9125 0.9125 0.9125 0.9125 0.9791
0.1371 14.0333 1200 0.2527 0.9225 0.9224 0.9249 0.9225 0.9817

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.0.1+cu118
  • Datasets 3.0.2
  • Tokenizers 0.20.1