ast-finetuned-audioset-10-10-0.4593-finetuned-gunshot
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9969
- Accuracy: 0.7412
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
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.398 | 1.0 | 341 | 1.3407 | 0.6059 |
| 1.0815 | 2.0 | 682 | 0.7835 | 0.7118 |
| 0.1502 | 3.0 | 1023 | 0.9741 | 0.6706 |
| 0.1563 | 4.0 | 1364 | 0.7744 | 0.7765 |
| 0.3851 | 5.0 | 1705 | 0.6325 | 0.8176 |
| 0.3527 | 6.0 | 2046 | 0.6877 | 0.7765 |
| 0.0537 | 7.0 | 2387 | 0.5326 | 0.7353 |
| 0.154 | 8.0 | 2728 | 0.7756 | 0.7824 |
| 0.0984 | 9.0 | 3069 | 0.9495 | 0.7412 |
| 0.3237 | 10.0 | 3410 | 0.9969 | 0.7412 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.1.dev0
- Tokenizers 0.20.3
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Model tree for Nama2024/ast-finetuned-audioset-10-10-0.4593-finetuned-gunshot
Base model
MIT/ast-finetuned-audioset-10-10-0.4593