pknayak / distilhubert-finetuned-gtzan

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Total runs: 159
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7-day runs: 158
30-day runs: 151
Model's Last Updated: 7月 31 2023
audio-classification

Introduction of distilhubert-finetuned-gtzan

Model Details of distilhubert-finetuned-gtzan

distilhubert-finetuned-gtzan

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

  • Loss: 0.5414
  • Accuracy: 0.87
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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.9502 1.0 113 1.7781 0.51
1.2616 2.0 226 1.1698 0.68
0.9512 3.0 339 0.8776 0.75
0.8453 4.0 452 0.8341 0.73
0.5448 5.0 565 0.6457 0.86
0.3014 6.0 678 0.7317 0.76
0.3948 7.0 791 0.5420 0.85
0.1436 8.0 904 0.5398 0.87
0.2 9.0 1017 0.5799 0.84
0.1685 10.0 1130 0.5414 0.87
Framework versions
  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.2
  • Tokenizers 0.13.3

Runs of pknayak distilhubert-finetuned-gtzan on huggingface.co

159
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0
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3-day runs
158
7-day runs
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