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metadata
license: apache-2.0
base_model: sanchit-gandhi/distilhubert-finetuned-gtzan-5-epochs
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: distilhubert-finetuned-gtzan-5-epochs-finetuned-gtzan-QUIZ
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: GTZAN
          type: marsyas/gtzan
          config: all
          split: train
          args: all
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.82

distilhubert-finetuned-gtzan-5-epochs-finetuned-gtzan-QUIZ

This model is a fine-tuned version of sanchit-gandhi/distilhubert-finetuned-gtzan-5-epochs on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6130
  • 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: 9e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 7
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.2256 0.9956 14 0.9755 0.68
0.9523 1.9911 28 0.8490 0.75
0.6907 2.9867 42 0.7725 0.78
0.5448 3.9822 56 0.6968 0.81
0.4604 4.9778 70 0.6409 0.81
0.4355 5.9733 84 0.6271 0.81
0.375 6.9689 98 0.6130 0.82

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1