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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_5-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_5-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: 1.2026
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- Accuracy: 0.6547
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- Sensitivity: 0.4720
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- Specificity: 0.8181
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- Score: 0.6451
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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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| 0.9246 | 1.0 | 258 | 0.9810 | 0.6076 | 0.5004 | 0.7035 | 0.6019 |
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| 0.8279 | 2.0 | 517 | 0.8591 | 0.6478 | 0.3691 | 0.8970 | 0.6331 |
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| 0.5969 | 3.0 | 776 | 0.9275 | 0.6446 | 0.5111 | 0.7639 | 0.6375 |
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| 0.185 | 4.0 | 1035 | 1.2026 | 0.6547 | 0.4720 | 0.8181 | 0.6451 |
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| 0.0305 | 4.99 | 1290 | 1.5138 | 0.6467 | 0.4873 | 0.7893 | 0.6383 |
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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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