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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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+
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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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+
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+ # ast_15-finetuned-ICBHI
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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