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: 0.5274
- Accuracy: 0.9
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: 12
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6838 | 1.0 | 57 | 0.5120 | 0.87 |
0.2759 | 2.0 | 114 | 0.4558 | 0.84 |
0.166 | 3.0 | 171 | 0.5021 | 0.84 |
0.252 | 4.0 | 228 | 0.3866 | 0.91 |
0.0299 | 5.0 | 285 | 0.3424 | 0.87 |
0.1403 | 6.0 | 342 | 0.6292 | 0.89 |
0.135 | 7.0 | 399 | 0.6622 | 0.91 |
0.0 | 8.0 | 456 | 0.7631 | 0.9 |
0.0 | 9.0 | 513 | 0.7565 | 0.89 |
0.0 | 10.0 | 570 | 0.5774 | 0.9 |
0.0 | 11.0 | 627 | 0.5556 | 0.9 |
0.0 | 12.0 | 684 | 0.5274 | 0.9 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.3.1
- Datasets 3.0.2
- Tokenizers 0.20.1
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Model tree for pppde/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
Base model
MIT/ast-finetuned-audioset-10-10-0.4593