ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan-finetuned-gtzan
This model is a fine-tuned version of ptah23/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.7839
- 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0007 | 1.0 | 112 | 0.7015 | 0.82 |
0.063 | 2.0 | 225 | 0.7797 | 0.82 |
0.1259 | 3.0 | 337 | 1.1225 | 0.83 |
0.0003 | 4.0 | 450 | 0.5694 | 0.89 |
0.0016 | 5.0 | 562 | 0.7449 | 0.89 |
0.0 | 6.0 | 675 | 0.9446 | 0.89 |
0.0 | 7.0 | 787 | 0.8780 | 0.88 |
0.0 | 8.0 | 900 | 0.7953 | 0.89 |
0.0988 | 9.0 | 1012 | 0.7962 | 0.9 |
0.0 | 9.96 | 1120 | 0.7839 | 0.9 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 1.13.1
- Datasets 2.14.3
- Tokenizers 0.13.2
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