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: 0.5321
- 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use 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: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
5.3547 | 0.9912 | 28 | 1.1577 | 0.73 |
2.8199 | 1.9823 | 56 | 0.7326 | 0.83 |
2.0591 | 2.9735 | 84 | 0.6054 | 0.87 |
1.5609 | 4.0 | 113 | 0.5425 | 0.89 |
1.5001 | 4.9558 | 140 | 0.5321 | 0.89 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1
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Model tree for eonrad/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
Base model
MIT/ast-finetuned-audioset-10-10-0.4593