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README.md
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# Training Logs
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## Summary metrics
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### Best ROUGE-1 score : **0.
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### Best ROUGE-2 score : **0.
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### Best ROUGE-L score : **0.
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## Wandb logs
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You can view the training logs [<img src="https://raw.githubusercontent.com/wandb/wandb/main/docs/README_images/logo-light.svg" width="200"/>](https://wandb.ai/william-derue/LLM-summarizer_trainer/runs/
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## Training details
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# Project details
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[<img src="https://avatars.githubusercontent.com/u/116890814?v=4" width="100"/>](https://github.com/WillIsback/Report_Maker)
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Fine-tuned on French audio podcast transcription data for summarization task. As a result, the model is able to summarize French audio podcast transcription data.
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The model will be used for
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It leverages state-of-the-art machine learning models to provide detailed and accurate reports.
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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# Training Logs
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## Summary metrics
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### Best ROUGE-1 score : **0.9842446709916588**
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### Best ROUGE-2 score : **0.9842154131847726**
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### Best ROUGE-L score : **0.9842446709916588**
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## Wandb logs
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You can view the training logs [<img src="https://raw.githubusercontent.com/wandb/wandb/main/docs/README_images/logo-light.svg" width="200"/>](https://wandb.ai/william-derue/LLM-summarizer_trainer/runs/s9xqw6o8).
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## Training details
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# Project details
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[<img src="https://avatars.githubusercontent.com/u/116890814?v=4" width="100"/>](https://github.com/WillIsback/Report_Maker)
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Fine-tuned on French audio podcast transcription data for summarization task. As a result, the model is able to summarize French audio podcast transcription data.
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The model will be used for an AI application: [Report Maker](https://github.com/WillIsback/Report_Maker) wich is a powerful tool designed to automate the process of transcribing and summarizing meetings.
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It leverages state-of-the-art machine learning models to provide detailed and accurate reports.
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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