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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: 0.9545454545454546 |
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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: 0.2288 |
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- Accuracy: 0.9545 |
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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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| 0.6417 | 1.0 | 33 | 0.5774 | 0.7879 | |
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| 0.4818 | 2.0 | 66 | 0.3792 | 0.8485 | |
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| 0.2756 | 3.0 | 99 | 0.3066 | 0.8788 | |
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| 0.3106 | 4.0 | 132 | 0.1951 | 0.9545 | |
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| 0.2138 | 5.0 | 165 | 0.2078 | 0.9394 | |
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| 0.0988 | 6.0 | 198 | 0.3227 | 0.9091 | |
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| 0.1043 | 7.0 | 231 | 0.2893 | 0.9394 | |
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| 0.0808 | 8.0 | 264 | 0.2177 | 0.9545 | |
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| 0.1312 | 9.0 | 297 | 0.2846 | 0.9091 | |
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| 0.0667 | 10.0 | 330 | 0.1955 | 0.9545 | |
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| 0.0513 | 11.0 | 363 | 0.2553 | 0.9545 | |
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| 0.0217 | 12.0 | 396 | 0.1708 | 0.9545 | |
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| 0.0136 | 13.0 | 429 | 0.1641 | 0.9545 | |
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| 0.0236 | 14.0 | 462 | 0.2203 | 0.9545 | |
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| 0.0097 | 15.0 | 495 | 0.2253 | 0.9545 | |
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| 0.003 | 16.0 | 528 | 0.2288 | 0.9545 | |
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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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