ast_15-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: 1.1688
- Accuracy: 0.5397
- Sensitivity: 0.2727
- Specificity: 0.7389
- Score: 0.5058
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: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score |
---|---|---|---|---|---|---|---|
0.7488 | 1.0 | 259 | 1.1831 | 0.5241 | 0.3551 | 0.6502 | 0.5027 |
0.7831 | 2.0 | 518 | 1.1688 | 0.5397 | 0.2727 | 0.7389 | 0.5058 |
0.7471 | 3.0 | 777 | 1.1593 | 0.5198 | 0.3772 | 0.6261 | 0.5017 |
0.5336 | 4.0 | 1036 | 1.4082 | 0.5281 | 0.3152 | 0.6869 | 0.5011 |
0.3833 | 5.0 | 1295 | 2.0232 | 0.4838 | 0.3840 | 0.5583 | 0.4712 |
0.1721 | 6.0 | 1554 | 2.5558 | 0.4893 | 0.3534 | 0.5906 | 0.4720 |
0.2745 | 7.0 | 1813 | 3.3175 | 0.4900 | 0.3917 | 0.5634 | 0.4775 |
0.0596 | 8.0 | 2072 | 3.6548 | 0.5143 | 0.3628 | 0.6274 | 0.4951 |
0.0034 | 9.0 | 2331 | 3.9119 | 0.5082 | 0.4053 | 0.5849 | 0.4951 |
0.0008 | 10.0 | 2590 | 4.3407 | 0.4875 | 0.4562 | 0.5108 | 0.4835 |
0.0 | 11.0 | 2849 | 4.1927 | 0.5136 | 0.3636 | 0.6255 | 0.4946 |
0.0 | 12.0 | 3108 | 4.2227 | 0.5111 | 0.3645 | 0.6204 | 0.4924 |
0.0 | 13.0 | 3367 | 4.2399 | 0.5114 | 0.3653 | 0.6204 | 0.4929 |
0.0 | 14.0 | 3626 | 4.2521 | 0.5114 | 0.3662 | 0.6198 | 0.4930 |
0.0 | 15.0 | 3885 | 4.2556 | 0.5114 | 0.3662 | 0.6198 | 0.4930 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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