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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-Recognition-ttoo |
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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: 0.9696969696969697 |
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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-Recognition-ttoo |
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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: 0.1858 |
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- Accuracy: 0.9697 |
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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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| 0.6477 | 1.0 | 33 | 0.5411 | 0.8182 | |
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| 0.5099 | 2.0 | 66 | 0.4458 | 0.7879 | |
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| 0.3855 | 3.0 | 99 | 0.5405 | 0.7727 | |
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| 0.2943 | 4.0 | 132 | 0.2268 | 0.9394 | |
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| 0.2818 | 5.0 | 165 | 0.2283 | 0.9091 | |
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| 0.2378 | 6.0 | 198 | 0.1955 | 0.9394 | |
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| 0.1321 | 7.0 | 231 | 0.2335 | 0.9394 | |
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| 0.1688 | 8.0 | 264 | 0.2009 | 0.9545 | |
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| 0.07 | 9.0 | 297 | 0.2629 | 0.9242 | |
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| 0.0413 | 10.0 | 330 | 0.2156 | 0.9545 | |
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| 0.0229 | 11.0 | 363 | 0.3189 | 0.9394 | |
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| 0.0062 | 12.0 | 396 | 0.3850 | 0.9242 | |
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| 0.0159 | 13.0 | 429 | 0.2462 | 0.9394 | |
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| 0.0179 | 14.0 | 462 | 0.1904 | 0.9697 | |
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| 0.0059 | 15.0 | 495 | 0.1844 | 0.9697 | |
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| 0.0248 | 16.0 | 528 | 0.1858 | 0.9697 | |
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### Framework versions |
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- Transformers 4.39.2 |
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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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