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metadata
license: apache-2.0
base_model: NemesisAlm/distilhubert-finetuned-gtzan
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: distilhubert-finetuned-gtzan
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: GTZAN
          type: marsyas/gtzan
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.88

distilhubert-finetuned-gtzan

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

  • Loss: 1.1532
  • Accuracy: 0.88

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-100
  • train_batch_size: 12
  • eval_batch_size: 12
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 1e-19
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0011 0.27 20 1.1532 0.88
0.0081 0.53 40 1.1532 0.88
0.0005 0.8 60 1.1532 0.88

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3