ast-finetuned-audioset-10-10-0.4593_ft_env_0-12
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: 0.3804
- Accuracy: 0.9643
- Precision: 0.9702
- Recall: 0.9643
- F1: 0.9643
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: 1.5e-06
- 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_steps: 56
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
2.0371 | 1.0 | 28 | 1.9267 | 0.1429 | 0.3214 | 0.1429 | 0.1482 |
1.7315 | 2.0 | 56 | 1.5823 | 0.3214 | 0.3667 | 0.3214 | 0.2973 |
1.3081 | 3.0 | 84 | 1.2250 | 0.75 | 0.8423 | 0.75 | 0.7499 |
0.9664 | 4.0 | 112 | 0.9526 | 0.8214 | 0.8616 | 0.8214 | 0.8078 |
0.6607 | 5.0 | 140 | 0.7525 | 0.8571 | 0.8795 | 0.8571 | 0.8520 |
0.5239 | 6.0 | 168 | 0.6080 | 0.8929 | 0.9152 | 0.8929 | 0.8866 |
0.453 | 7.0 | 196 | 0.5089 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
0.323 | 8.0 | 224 | 0.4353 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
0.296 | 9.0 | 252 | 0.3804 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
0.2167 | 10.0 | 280 | 0.3382 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
0.186 | 11.0 | 308 | 0.3157 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
0.1748 | 12.0 | 336 | 0.2931 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
0.1367 | 13.0 | 364 | 0.2781 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
0.1469 | 14.0 | 392 | 0.2705 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
0.1308 | 15.0 | 420 | 0.2679 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.11.0
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