cleandata / distilhubert-finetuned-gtzan_accuracy_93

huggingface.co
Total runs: 173
24-hour runs: -1
7-day runs: 10
30-day runs: 168
Model's Last Updated: 2023年7月5日
audio-classification

Introduction of distilhubert-finetuned-gtzan_accuracy_93

Model Details of distilhubert-finetuned-gtzan_accuracy_93

distilhubert-finetuned-gtzan_accuracy_93

This model is a fine-tuned version of yuval6967/distilhubert-finetuned-gtzan on the GTZAN dataset.

It achieves the following results on the evaluation set:

  • Loss: 0.5121
  • Accuracy: 0.93
Model description
Intended uses & limitations
  • Model is built to identify the genre of music based on a ~30 sec clip
Training and evaluation data

More information needed

Training procedure
  • test_size = 0.20 was used for the split
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
0.0316 1.0 100 0.4338 0.895
0.0031 2.0 200 0.7039 0.86
0.0069 3.0 300 0.4526 0.925
0.1799 4.0 400 0.7071 0.88
0.1783 5.0 500 0.5923 0.92
0.0011 6.0 600 0.5498 0.92
0.0005 7.0 700 0.4927 0.925
0.0005 8.0 800 0.6172 0.915
0.0004 9.0 900 0.4988 0.925
0.0004 10.0 1000 0.5121 0.93
Framework versions
  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3

Runs of cleandata distilhubert-finetuned-gtzan_accuracy_93 on huggingface.co

173
Total runs
-1
24-hour runs
0
3-day runs
10
7-day runs
168
30-day runs

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