apv53-finetuned-gtzan

This model is a fine-tuned version of OthmaneJ/distil-wav2vec2 on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7427
  • Accuracy: 0.82

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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_ratio: 0.1
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.8074 1.0 113 1.1764 0.63
0.8226 2.0 226 0.8222 0.73
0.8055 3.0 339 0.9653 0.74
0.5099 4.0 452 1.3430 0.59
0.6568 5.0 565 0.8467 0.76
0.5449 6.0 678 0.9551 0.76
0.3872 7.0 791 0.8185 0.81
0.3452 8.0 904 0.8198 0.82
0.1398 9.0 1017 0.7110 0.85
0.1282 10.0 1130 0.7427 0.82

Framework versions

  • Transformers 4.48.0.dev0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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Dataset used to train apv53-fit/distil-wav2vec2-finetuned-gtzan

Evaluation results