ast-audio-certficate-unit4
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6726
- Accuracy: 0.89
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6707 | 1.0 | 57 | 0.6816 | 0.73 |
| 0.231 | 2.0 | 114 | 0.5718 | 0.81 |
| 0.181 | 3.0 | 171 | 0.5930 | 0.82 |
| 0.0275 | 4.0 | 228 | 0.4938 | 0.87 |
| 0.0049 | 5.0 | 285 | 0.6563 | 0.86 |
| 0.013 | 6.0 | 342 | 0.9035 | 0.82 |
| 0.1423 | 7.0 | 399 | 0.4829 | 0.9 |
| 0.0 | 8.0 | 456 | 0.7405 | 0.91 |
| 0.0 | 9.0 | 513 | 0.6386 | 0.89 |
| 0.0 | 10.0 | 570 | 0.6726 | 0.89 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for aoussou/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
Base model
MIT/ast-finetuned-audioset-10-10-0.4593