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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-555 |
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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: 0.9247311827956989 |
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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-555 |
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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: 0.4156 |
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- Accuracy: 0.9247 |
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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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| 0.6428 | 1.0 | 46 | 0.6271 | 0.7204 | |
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| 0.4622 | 2.0 | 92 | 0.4054 | 0.8602 | |
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| 0.3098 | 3.0 | 138 | 0.5667 | 0.8172 | |
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| 0.2696 | 4.0 | 184 | 0.4179 | 0.8817 | |
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| 0.2806 | 5.0 | 230 | 0.4129 | 0.8710 | |
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| 0.2078 | 6.0 | 276 | 0.3541 | 0.9140 | |
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| 0.1652 | 7.0 | 322 | 0.3338 | 0.9140 | |
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| 0.0871 | 8.0 | 368 | 0.4072 | 0.9140 | |
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| 0.1267 | 9.0 | 414 | 0.3649 | 0.9247 | |
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| 0.0651 | 10.0 | 460 | 0.3436 | 0.9355 | |
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| 0.0976 | 11.0 | 506 | 0.4163 | 0.9140 | |
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| 0.0186 | 12.0 | 552 | 0.4164 | 0.9247 | |
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| 0.0324 | 13.0 | 598 | 0.4156 | 0.9247 | |
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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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