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README.md
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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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- precision
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- recall
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- f1
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model-index:
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- name: ast-finetuned-audioset-10-10-0.4593_ft_env_0-12
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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-finetuned-audioset-10-10-0.4593_ft_env_0-12
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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: 0.3804
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- Accuracy: 0.9643
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- Precision: 0.9702
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- Recall: 0.9643
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- F1: 0.9643
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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: 1.5e-06
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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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_steps: 56
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 2.0371 | 1.0 | 28 | 1.9267 | 0.1429 | 0.3214 | 0.1429 | 0.1482 |
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| 1.7315 | 2.0 | 56 | 1.5823 | 0.3214 | 0.3667 | 0.3214 | 0.2973 |
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| 1.3081 | 3.0 | 84 | 1.2250 | 0.75 | 0.8423 | 0.75 | 0.7499 |
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| 0.9664 | 4.0 | 112 | 0.9526 | 0.8214 | 0.8616 | 0.8214 | 0.8078 |
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| 0.6607 | 5.0 | 140 | 0.7525 | 0.8571 | 0.8795 | 0.8571 | 0.8520 |
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| 0.5239 | 6.0 | 168 | 0.6080 | 0.8929 | 0.9152 | 0.8929 | 0.8866 |
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| 0.453 | 7.0 | 196 | 0.5089 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
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| 0.323 | 8.0 | 224 | 0.4353 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
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| 0.296 | 9.0 | 252 | 0.3804 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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| 0.2167 | 10.0 | 280 | 0.3382 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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| 0.186 | 11.0 | 308 | 0.3157 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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| 0.1748 | 12.0 | 336 | 0.2931 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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| 0.1367 | 13.0 | 364 | 0.2781 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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| 0.1469 | 14.0 | 392 | 0.2705 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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| 0.1308 | 15.0 | 420 | 0.2679 | 0.9643 | 0.9702 | 0.9643 | 0.9643 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0
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- Datasets 2.10.1
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- Tokenizers 0.11.0
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