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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: deeepfake-audio-A |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8939393939393939 |
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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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# deeepfake-audio-A |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5791 |
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- Accuracy: 0.8939 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 0.01 |
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- num_epochs: 16 |
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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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| 0.638 | 1.0 | 33 | 0.6019 | 0.7121 | |
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| 0.4734 | 2.0 | 66 | 0.4665 | 0.8333 | |
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| 0.4281 | 3.0 | 99 | 0.3324 | 0.8939 | |
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| 0.2556 | 4.0 | 132 | 0.4255 | 0.8788 | |
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| 0.196 | 5.0 | 165 | 0.4007 | 0.8939 | |
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| 0.1557 | 6.0 | 198 | 0.3592 | 0.9091 | |
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| 0.0951 | 7.0 | 231 | 0.4533 | 0.9091 | |
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| 0.0505 | 8.0 | 264 | 0.3741 | 0.9242 | |
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| 0.0475 | 9.0 | 297 | 0.7494 | 0.8333 | |
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| 0.0394 | 10.0 | 330 | 0.7242 | 0.8636 | |
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| 0.0034 | 11.0 | 363 | 0.7240 | 0.8636 | |
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| 0.041 | 12.0 | 396 | 0.7503 | 0.8485 | |
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| 0.0028 | 13.0 | 429 | 0.6365 | 0.8939 | |
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| 0.0189 | 14.0 | 462 | 0.5352 | 0.9091 | |
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| 0.0041 | 15.0 | 495 | 0.5700 | 0.9091 | |
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| 0.0023 | 16.0 | 528 | 0.5791 | 0.8939 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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