exp_1715025412
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6403
- Accuracy: 0.8974
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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 60
- 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 |
|---|---|---|---|---|
| 0.5131 | 0.9856 | 41 | 0.4401 | 0.8157 |
| 0.2645 | 1.9952 | 83 | 0.3510 | 0.875 |
| 0.2224 | 2.9808 | 124 | 0.3333 | 0.8910 |
| 0.1223 | 3.9904 | 166 | 0.4310 | 0.8830 |
| 0.0721 | 5.0 | 208 | 0.5080 | 0.8830 |
| 0.0059 | 5.9856 | 249 | 0.6021 | 0.8910 |
| 0.001 | 6.9952 | 291 | 0.6082 | 0.8878 |
| 0.0004 | 7.9808 | 332 | 0.6385 | 0.8942 |
| 0.0002 | 8.9904 | 374 | 0.6386 | 0.8958 |
| 0.0003 | 9.8558 | 410 | 0.6403 | 0.8974 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
MIT/ast-finetuned-audioset-10-10-0.4593