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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: hubert-large-ls960-ft-finetuned-gtzan
    results: []

hubert-large-ls960-ft-finetuned-gtzan

This model is a fine-tuned version of facebook/hubert-large-ls960-ft on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8531
  • Accuracy: 0.78

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: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.279 1.0 112 2.2924 0.08
2.0905 2.0 225 2.0931 0.31
1.7503 3.0 337 1.6857 0.46
1.7021 4.0 450 1.5041 0.54
1.3693 5.0 562 1.4453 0.53
1.1515 6.0 675 1.2720 0.62
1.0195 7.0 787 1.2036 0.61
0.8957 8.0 900 1.1265 0.62
0.9654 9.0 1012 1.0117 0.68
1.0166 10.0 1125 0.9691 0.68
0.8868 11.0 1237 1.0249 0.69
0.8822 12.0 1350 0.9859 0.69
0.808 13.0 1462 0.8248 0.75
0.7107 14.0 1575 0.9660 0.71
0.7964 15.0 1687 0.8939 0.73
0.69 16.0 1800 0.8490 0.75
0.4321 17.0 1912 0.8282 0.77
0.4942 18.0 2025 0.8220 0.78
0.4275 19.0 2137 0.8435 0.79
0.4661 19.91 2240 0.8531 0.78

Framework versions

  • Transformers 4.30.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3