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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_13-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_13-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: 1.0981
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- Accuracy: 0.5811
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- Sensitivity: 0.0484
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- Specificity: 0.9785
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- Score: 0.5134
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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: 5
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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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| 1.0311 | 1.0 | 259 | 1.0981 | 0.5811 | 0.0484 | 0.9785 | 0.5134 |
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| 1.1378 | 2.0 | 518 | 1.0778 | 0.5800 | 0.1427 | 0.9062 | 0.5245 |
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| 1.0184 | 3.0 | 777 | 1.0696 | 0.5779 | 0.1495 | 0.8973 | 0.5234 |
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| 1.0743 | 4.0 | 1036 | 1.0705 | 0.5757 | 0.1946 | 0.8599 | 0.5273 |
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| 0.9974 | 5.0 | 1295 | 1.0692 | 0.5789 | 0.1963 | 0.8644 | 0.5303 |
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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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