Carlos Rosas
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Update README.md
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README.md
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@@ -6,6 +6,14 @@ Cassandre-RAG is a fine-tuned llama-3.1-8b model, built for RAG on French admini
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The model was trained on a H100, using these parameters:
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### Training Hyperparameters
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- Max Steps: 3000
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- Learning Rate: 3e-4
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The model was trained on a H100, using these parameters:
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## Training Data
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The model was fine-tuned on a specialized corpus consisting of:
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1. Synthetic queries: Generated from chunks of text extracted from French administrative documents.
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2. Retrieved documents: For each synthetic query, relevant documents were retrieved using the BM25 ranking algorithm.
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3. Generated answers: Responses to the synthetic queries were created based on the retrieved documents.
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### Training Hyperparameters
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- Max Steps: 3000
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- Learning Rate: 3e-4
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