ast_binary_7-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: 0.7561
- Accuracy: 0.5764
- Sensitivity: 0.6185
- Specificity: 0.5450
- Score: 0.5818
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: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score |
---|---|---|---|---|---|---|---|
0.6321 | 1.0 | 259 | 0.7561 | 0.5764 | 0.6185 | 0.5450 | 0.5818 |
0.5672 | 2.0 | 518 | 0.8579 | 0.5626 | 0.6015 | 0.5336 | 0.5676 |
0.5443 | 3.0 | 777 | 1.0517 | 0.5074 | 0.8275 | 0.2687 | 0.5481 |
0.5075 | 4.0 | 1036 | 0.9977 | 0.5358 | 0.7638 | 0.3657 | 0.5647 |
0.4912 | 5.0 | 1295 | 1.2474 | 0.4969 | 0.8539 | 0.2307 | 0.5423 |
0.4331 | 6.0 | 1554 | 1.0732 | 0.5376 | 0.7077 | 0.4106 | 0.5592 |
0.4368 | 7.0 | 1813 | 1.0947 | 0.5405 | 0.7230 | 0.4043 | 0.5637 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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