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--- |
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base_model: microsoft/wavlm-base |
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tags: |
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- audio-classification |
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- deepfake |
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- audio-spoof |
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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: wavlm-base-960h-asv19-deepfake |
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results: [] |
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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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# wavlm-base-960h-asv19-deepfake |
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This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0332 |
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- Accuracy: 0.9950 |
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- Far: 0.0416 |
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- Frr: 0.0009 |
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- Eer: 0.0212 |
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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: 1e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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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- num_epochs: 2.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Far | Frr | Eer | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:| |
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| 0.2408 | 0.39 | 2500 | 0.0574 | 0.9889 | 0.0863 | 0.0025 | 0.0444 | |
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| 0.0372 | 0.79 | 5000 | 0.0524 | 0.9901 | 0.0914 | 0.0006 | 0.0460 | |
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| 0.0231 | 1.18 | 7500 | 0.0539 | 0.9912 | 0.0824 | 0.0004 | 0.0414 | |
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| 0.0213 | 1.58 | 10000 | 0.0301 | 0.9951 | 0.0361 | 0.0013 | 0.0187 | |
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| 0.0191 | 1.97 | 12500 | 0.0332 | 0.9950 | 0.0416 | 0.0009 | 0.0212 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.2 |
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