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trainer
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: 0.3684
- Accuracy: 0.9275
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.2624 | 2.0 | 50 | 0.3928 | 0.88 |
| 0.9069 | 4.0 | 100 | 0.3259 | 0.9025 |
| 0.9069 | 6.0 | 150 | 0.2775 | 0.93 |
| 0.0567 | 8.0 | 200 | 0.3220 | 0.9075 |
| 0.0567 | 10.0 | 250 | 0.3196 | 0.9075 |
| 0.0109 | 12.0 | 300 | 0.3644 | 0.9175 |
| 0.0109 | 14.0 | 350 | 0.3501 | 0.93 |
| 0.0138 | 16.0 | 400 | 0.3569 | 0.9275 |
| 0.0138 | 18.0 | 450 | 0.3700 | 0.9225 |
| 0.0006 | 20.0 | 500 | 0.3662 | 0.925 |
| 0.0006 | 22.0 | 550 | 0.3669 | 0.925 |
| 0.0002 | 24.0 | 600 | 0.3673 | 0.925 |
| 0.0002 | 26.0 | 650 | 0.3677 | 0.925 |
| 0.0002 | 28.0 | 700 | 0.3679 | 0.9275 |
| 0.0002 | 30.0 | 750 | 0.3680 | 0.9275 |
| 0.0002 | 32.0 | 800 | 0.3681 | 0.9275 |
| 0.0002 | 34.0 | 850 | 0.3684 | 0.9275 |
| 0.0002 | 36.0 | 900 | 0.3683 | 0.9275 |
| 0.0002 | 38.0 | 950 | 0.3684 | 0.9275 |
| 0.0002 | 40.0 | 1000 | 0.3684 | 0.9275 |
Framework versions
- Transformers 4.27.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
