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metadata
license: apache-2.0
base_model: saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-gtzan
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: GTZAN
          type: marsyas/gtzan
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.805

wav2vec2-base-finetuned-gtzan

This model is a fine-tuned version of saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2 on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7271
  • Accuracy: 0.805

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0116 1.0 25 1.0805 0.715
0.7603 2.0 50 1.0321 0.76
0.6462 3.0 75 0.8840 0.775
0.5343 4.0 100 0.8303 0.78
0.4705 5.0 125 0.9837 0.72
0.3806 6.0 150 0.8099 0.79
0.3126 7.0 175 0.7897 0.79
0.2727 8.0 200 0.6896 0.81
0.2301 9.0 225 0.7518 0.81
0.2138 10.0 250 0.7271 0.805

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2