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--- |
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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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datasets: |
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- Nooon/Donate_a_cry |
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metrics: |
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- accuracy |
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model-index: |
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- name: ast-finetuned-cry |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: DonateACry |
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type: Nooon/Donate_a_cry |
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config: train |
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split: train |
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args: train |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5454545454545454 |
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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-cry |
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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 DonateACry dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6404 |
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- Accuracy: 0.5455 |
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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: 2e-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: 2 |
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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_ratio: 0.05 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.6297 | 1.0 | 11 | 1.6891 | 0.3636 | |
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| 1.1137 | 2.0 | 22 | 1.3156 | 0.4545 | |
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| 0.5047 | 3.0 | 33 | 1.3955 | 0.4545 | |
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| 0.2062 | 4.0 | 44 | 1.4002 | 0.6364 | |
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| 0.0613 | 5.0 | 55 | 1.6693 | 0.5455 | |
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| 0.0142 | 6.0 | 66 | 1.3452 | 0.6364 | |
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| 0.0053 | 7.0 | 77 | 1.6914 | 0.5455 | |
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| 0.0038 | 8.0 | 88 | 1.6689 | 0.5455 | |
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| 0.0027 | 9.0 | 99 | 1.6357 | 0.5455 | |
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| 0.002 | 10.0 | 110 | 1.6404 | 0.5455 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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