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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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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-finetuned-ks |
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results: |
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- task: |
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name: DeepFake audio detection |
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type: audio-classification |
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dataset: |
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name: Fake or Real |
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type: Audio |
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config: default |
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split: validation |
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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: 0.9994443415447305 |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: audio-classification |
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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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# wav2vec2-base-finetuned-ks |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the Fake or Real (FoR) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0031 |
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- Accuracy: 0.9994 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 0.1 |
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- num_epochs: 5 |
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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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| 0.0085 | 1.0 | 421 | 0.0133 | 0.9977 | |
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| 0.0005 | 2.0 | 842 | 0.0060 | 0.9986 | |
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| 0.0002 | 3.0 | 1263 | 0.0031 | 0.9994 | |
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| 0.0002 | 4.0 | 1684 | 0.0033 | 0.9993 | |
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| 0.0001 | 5.0 | 2105 | 0.0028 | 0.9994 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
