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wav2vec2-base-960h-finetuned-gtzan

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0690
  • Accuracy: 0.73

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: 3e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.3011 0.9956 56 2.2915 0.1
2.2365 1.9911 112 2.1198 0.37
1.9162 2.9867 168 1.9024 0.42
1.7154 4.0 225 1.7397 0.39
1.757 4.9956 281 1.5732 0.47
1.546 5.9911 337 1.5172 0.47
1.5738 6.9867 393 1.3950 0.54
1.2893 8.0 450 1.4202 0.56
1.2745 8.9956 506 1.2819 0.59
1.2632 9.9911 562 1.2788 0.66
1.2195 10.9867 618 1.1909 0.63
1.1151 12.0 675 1.1605 0.62
1.0165 12.9956 731 1.1202 0.67
0.9418 13.9911 787 1.0747 0.73
0.9686 14.9333 840 1.0690 0.73

Framework versions

  • Transformers 4.43.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Finetuned from

Dataset used to train deeeed/wav2vec2-base-960h-finetuned-gtzan

Evaluation results