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--- |
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license: bsd-3-clause |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: ast_15-finetuned-ICBHI |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ast_15-finetuned-ICBHI |
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This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1688 |
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- Accuracy: 0.5397 |
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- Sensitivity: 0.2727 |
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- Specificity: 0.7389 |
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- Score: 0.5058 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:| |
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| 0.7488 | 1.0 | 259 | 1.1831 | 0.5241 | 0.3551 | 0.6502 | 0.5027 | |
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| 0.7831 | 2.0 | 518 | 1.1688 | 0.5397 | 0.2727 | 0.7389 | 0.5058 | |
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| 0.7471 | 3.0 | 777 | 1.1593 | 0.5198 | 0.3772 | 0.6261 | 0.5017 | |
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| 0.5336 | 4.0 | 1036 | 1.4082 | 0.5281 | 0.3152 | 0.6869 | 0.5011 | |
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| 0.3833 | 5.0 | 1295 | 2.0232 | 0.4838 | 0.3840 | 0.5583 | 0.4712 | |
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| 0.1721 | 6.0 | 1554 | 2.5558 | 0.4893 | 0.3534 | 0.5906 | 0.4720 | |
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| 0.2745 | 7.0 | 1813 | 3.3175 | 0.4900 | 0.3917 | 0.5634 | 0.4775 | |
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| 0.0596 | 8.0 | 2072 | 3.6548 | 0.5143 | 0.3628 | 0.6274 | 0.4951 | |
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| 0.0034 | 9.0 | 2331 | 3.9119 | 0.5082 | 0.4053 | 0.5849 | 0.4951 | |
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| 0.0008 | 10.0 | 2590 | 4.3407 | 0.4875 | 0.4562 | 0.5108 | 0.4835 | |
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| 0.0 | 11.0 | 2849 | 4.1927 | 0.5136 | 0.3636 | 0.6255 | 0.4946 | |
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| 0.0 | 12.0 | 3108 | 4.2227 | 0.5111 | 0.3645 | 0.6204 | 0.4924 | |
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| 0.0 | 13.0 | 3367 | 4.2399 | 0.5114 | 0.3653 | 0.6204 | 0.4929 | |
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| 0.0 | 14.0 | 3626 | 4.2521 | 0.5114 | 0.3662 | 0.6198 | 0.4930 | |
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| 0.0 | 15.0 | 3885 | 4.2556 | 0.5114 | 0.3662 | 0.6198 | 0.4930 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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