ast_8-finetuned-ICBHI
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: 1.1190
- Accuracy: 0.6641
- Sensitivity: 0.4474
- Specificity: 0.8579
- Score: 0.6527
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score |
---|---|---|---|---|---|---|---|
0.9271 | 1.0 | 258 | 1.0487 | 0.5793 | 0.5480 | 0.6074 | 0.5777 |
0.8124 | 2.0 | 517 | 0.8780 | 0.6366 | 0.3369 | 0.9046 | 0.6208 |
0.714 | 3.0 | 776 | 0.9018 | 0.6482 | 0.5510 | 0.7351 | 0.6431 |
0.2385 | 4.0 | 1035 | 1.1190 | 0.6641 | 0.4474 | 0.8579 | 0.6527 |
0.0712 | 4.99 | 1290 | 1.3453 | 0.6594 | 0.5173 | 0.7865 | 0.6519 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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