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whisper-base.en-finetuned-gtzan
This model is a fine-tuned version of openai/whisper-base.en on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6266
- 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: 5e-05
- 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: 0.1
- num_epochs: 18
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7396 | 1.0 | 75 | 1.6061 | 0.56 |
| 0.8839 | 2.0 | 150 | 0.8286 | 0.77 |
| 0.7631 | 3.0 | 225 | 0.6353 | 0.81 |
| 0.4049 | 4.0 | 300 | 0.5840 | 0.82 |
| 0.3031 | 5.0 | 375 | 0.4069 | 0.88 |
| 0.3031 | 6.0 | 450 | 0.7152 | 0.81 |
| 0.2879 | 7.0 | 525 | 0.7061 | 0.85 |
| 0.0301 | 8.0 | 600 | 0.5691 | 0.89 |
| 0.0311 | 9.0 | 675 | 0.6153 | 0.88 |
| 0.0025 | 10.0 | 750 | 0.5463 | 0.88 |
| 0.0036 | 11.0 | 825 | 0.6017 | 0.89 |
| 0.0016 | 12.0 | 900 | 0.6859 | 0.85 |
| 0.0014 | 13.0 | 975 | 0.5887 | 0.89 |
| 0.0012 | 14.0 | 1050 | 0.6525 | 0.9 |
| 0.0011 | 15.0 | 1125 | 0.6289 | 0.89 |
| 0.0011 | 16.0 | 1200 | 0.6277 | 0.88 |
| 0.001 | 17.0 | 1275 | 0.6274 | 0.88 |
| 0.0611 | 18.0 | 1350 | 0.6266 | 0.88 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
