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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_22-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_22-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: 2.5036
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- Accuracy: 0.6867
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- Sensitivity: 0.5346
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- Specificity: 0.8228
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- Score: 0.6787
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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: 10
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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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| 1.0662 | 1.0 | 345 | 0.9169 | 0.6389 | 0.3963 | 0.8558 | 0.6260 |
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| 0.7055 | 2.0 | 690 | 0.8638 | 0.6512 | 0.4516 | 0.8297 | 0.6406 |
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| 0.5748 | 3.0 | 1035 | 0.9060 | 0.6599 | 0.4409 | 0.8558 | 0.6483 |
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| 0.3318 | 4.0 | 1380 | 1.1034 | 0.6555 | 0.3641 | 0.9162 | 0.6401 |
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| 0.1411 | 5.0 | 1725 | 1.3586 | 0.6838 | 0.5346 | 0.8173 | 0.6759 |
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| 0.0854 | 6.0 | 2070 | 2.1432 | 0.6759 | 0.4608 | 0.8681 | 0.6645 |
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| 0.0186 | 7.0 | 2415 | 2.3421 | 0.6715 | 0.5545 | 0.7761 | 0.6653 |
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| 0.0417 | 8.0 | 2760 | 2.4426 | 0.6824 | 0.5361 | 0.8132 | 0.6746 |
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| 0.0001 | 9.0 | 3105 | 2.4895 | 0.6831 | 0.5346 | 0.8159 | 0.6752 |
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| 0.0 | 10.0 | 3450 | 2.5036 | 0.6867 | 0.5346 | 0.8228 | 0.6787 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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