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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_8-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_8-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: 1.1190
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- Accuracy: 0.6641
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- Sensitivity: 0.4474
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- Specificity: 0.8579
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- Score: 0.6527
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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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| 0.9271 | 1.0 | 258 | 1.0487 | 0.5793 | 0.5480 | 0.6074 | 0.5777 |
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| 0.8124 | 2.0 | 517 | 0.8780 | 0.6366 | 0.3369 | 0.9046 | 0.6208 |
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| 0.714 | 3.0 | 776 | 0.9018 | 0.6482 | 0.5510 | 0.7351 | 0.6431 |
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| 0.2385 | 4.0 | 1035 | 1.1190 | 0.6641 | 0.4474 | 0.8579 | 0.6527 |
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| 0.0712 | 4.99 | 1290 | 1.3453 | 0.6594 | 0.5173 | 0.7865 | 0.6519 |
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### Framework versions
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- Transformers 4.30.0.dev0
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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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