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--- |
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library_name: transformers |
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license: bsd-3-clause |
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base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
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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: revix_classifier |
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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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# revix_classifier |
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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: 0.4733 |
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- Accuracy: 0.9292 |
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- Precision: 0.9492 |
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- Recall: 0.9106 |
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- F1: 0.9295 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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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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| 0.4055 | 1.0 | 120 | 0.4456 | 0.8 | 0.7698 | 0.8699 | 0.8168 | |
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| 0.4578 | 2.0 | 240 | 0.4217 | 0.875 | 0.8345 | 0.9431 | 0.8855 | |
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| 0.2235 | 3.0 | 360 | 0.4959 | 0.85 | 0.9780 | 0.7236 | 0.8318 | |
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| 0.092 | 4.0 | 480 | 0.3820 | 0.9083 | 0.9391 | 0.8780 | 0.9076 | |
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| 0.2152 | 5.0 | 600 | 0.5537 | 0.8792 | 0.8615 | 0.9106 | 0.8854 | |
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| 0.0612 | 6.0 | 720 | 0.4747 | 0.9292 | 0.9417 | 0.9187 | 0.9300 | |
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| 0.0382 | 7.0 | 840 | 0.4424 | 0.925 | 0.9412 | 0.9106 | 0.9256 | |
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| 0.0015 | 8.0 | 960 | 0.4647 | 0.925 | 0.9646 | 0.8862 | 0.9237 | |
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| 0.0005 | 9.0 | 1080 | 0.4684 | 0.9292 | 0.9492 | 0.9106 | 0.9295 | |
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| 0.0006 | 10.0 | 1200 | 0.4733 | 0.9292 | 0.9492 | 0.9106 | 0.9295 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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