distilhubert-ft-keyword-spotting-finetuned-gtzan
This model is a fine-tuned version of anton-l/distilhubert-ft-keyword-spotting on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.8447
- Accuracy: 0.75
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.563 | 1.0 | 113 | 1.3582 | 0.64 |
| 0.9967 | 2.0 | 226 | 0.9973 | 0.72 |
| 0.872 | 3.0 | 339 | 0.8447 | 0.75 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3