Adbhut / wav2vec2-base-finetuned-gtzan

huggingface.co
Total runs: 182
24-hour runs: 8
7-day runs: 16
30-day runs: 163
Model's Last Updated: Septiembre 10 2023
audio-classification

Introduction of wav2vec2-base-finetuned-gtzan

Model Details of wav2vec2-base-finetuned-gtzan

wav2vec2-base-finetuned-gtzan

This model is a fine-tuned version of facebook/wav2vec2-base on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Accuracy: 0.91
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
0.4667 1.0 113 0.7013 0.79
0.6329 2.0 226 1.1081 0.69
0.151 3.0 339 0.6619 0.84
0.2903 4.0 452 0.8713 0.78
0.379 5.0 565 0.7113 0.85
0.1222 6.0 678 0.6789 0.87
0.292 7.0 791 0.6808 0.88
0.0305 8.0 904 0.5518 0.91
0.0073 9.0 1017 0.7742 0.88
0.007 10.0 1130 0.7251 0.88
Framework versions
  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3

Runs of Adbhut wav2vec2-base-finetuned-gtzan on huggingface.co

182
Total runs
8
24-hour runs
17
3-day runs
16
7-day runs
163
30-day runs

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wav2vec2-base-finetuned-gtzan install

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