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Update README.md
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README.md
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@@ -3,19 +3,17 @@ 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: wav2vec2-base-finetuned-ks
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results:
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- task:
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name:
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type: audio-classification
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dataset:
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name:
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type:
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config: default
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split: validation
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args: default
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- name: Accuracy
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type: accuracy
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value: 0.9994443415447305
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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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@@ -30,7 +32,7 @@ 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
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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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- 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
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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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- 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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# 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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- 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
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