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whisper-medium.en-finetuned-gtzan

This model is a fine-tuned version of openai/whisper-medium.en on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2885
  • Accuracy: 0.95

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 16
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7711 1.0 112 1.6556 0.52
0.5477 2.0 225 0.4738 0.85
0.535 3.0 337 0.3137 0.92
0.231 4.0 450 0.3613 0.9
0.1923 5.0 562 0.2885 0.95
0.0584 6.0 675 0.6531 0.86
0.1783 7.0 787 0.5717 0.9
0.0022 8.0 900 0.4205 0.91
0.1032 9.0 1012 0.4984 0.91
0.0011 10.0 1125 0.3778 0.94
0.0104 11.0 1237 0.3709 0.94
0.0011 12.0 1350 0.4564 0.92
0.0009 13.0 1462 0.3796 0.94
0.0008 14.0 1575 0.3880 0.94
0.0008 15.0 1687 0.3930 0.94
0.0008 15.93 1792 0.3955 0.94

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Evaluation results