| --- |
| library_name: transformers |
| license: bsd-3-clause |
| base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: AST_ESC50_FineTuned |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # AST_ESC50_FineTuned |
|
|
| 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 an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2868 |
| - Accuracy: 1.0 |
|
|
| ## Model description |
|
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| More information needed |
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|
| ## Intended uses & limitations |
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| More information needed |
|
|
| ## 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: |
| - learning_rate: 3e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 5 | 0.9597 | 0.9 | |
| | 1.1896 | 2.0 | 10 | 0.4110 | 1.0 | |
| | 1.1896 | 3.0 | 15 | 0.2868 | 1.0 | |
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| ### Framework versions |
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|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 5.0.0 |
| - Tokenizers 0.22.2 |
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|
