ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
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: 0.4104
- 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.017 | 1.0 | 29 | 0.6152 | 0.84 |
0.3871 | 2.0 | 58 | 0.6296 | 0.77 |
0.123 | 3.0 | 87 | 0.5262 | 0.83 |
0.0729 | 4.0 | 116 | 0.5441 | 0.83 |
0.0109 | 5.0 | 145 | 0.3967 | 0.9 |
0.0037 | 6.0 | 174 | 0.3975 | 0.88 |
0.0063 | 7.0 | 203 | 0.4177 | 0.89 |
0.0014 | 8.0 | 232 | 0.4248 | 0.89 |
0.0011 | 9.0 | 261 | 0.4160 | 0.89 |
0.0012 | 10.0 | 290 | 0.4104 | 0.89 |
Framework versions
- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
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MIT/ast-finetuned-audioset-10-10-0.4593