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README.md
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yassmenyoussef55-arete-global/huggingface/runs/gt6e5ppa)
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# mixed_model_finetuned_cremad
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This model is a fine-tuned version of wav2vec2 on audio stream part and
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It achieves the following results on the evaluation set:
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- Loss: 0.3098
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- Accuracy: 0.8972
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yassmenyoussef55-arete-global/huggingface/runs/gt6e5ppa)
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# mixed_model_finetuned_cremad
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This model is a fine-tuned version of wav2vec2 on audio stream part and pretrained resnet3d_101 on video stream part ,[](https://huggingface.co/)
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It was trained from scratch on [CremaD dataset](https://github.com/CheyneyComputerScience/CREMA-D).
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This dataset provides 7442 samples of recordings from actors performing on 6 different emotions in English, which are:
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```python
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emotions = ['angry', 'disgust', 'fearful', 'happy', 'neutral', 'sad']
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```
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It achieves the following results on the evaluation set:
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- Loss: 0.3098
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- Accuracy: 0.8972
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