| --- |
| license: apache-2.0 |
| pipeline_tag: audio-classification |
| base_model: facebook/wav2vec2-base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - audiofolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: Deeepfake-audio |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: audiofolder |
| type: audiofolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9545454545454546 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # deeepfake-audio-Recognition |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2288 |
| - Accuracy: 0.9545 |
|
|
| ## Model description |
|
|
| * The model is fintune on facebook/wav2vec2-base |
|
|
|
|
| ## Intended uses & limitations |
|
|
| * The model still needs dataset to increase model accuracy. |
| ## Training and evaluation data |
|
|
| * The model is trained on multi-ethnic english dataset. |
| * The input audio dataset is about 16KHz. |
|
|
| ### Framework versions |
|
|
| - Transformers 4.39.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
