BioMistral-CPT-SFT-7B is a French medical language model based on BioMistral-7B, adapted for French medical domain applications through a combined approach of Continual Pre-Training (CPT) followed by Supervised Fine-Tuning (SFT).
Model Details
Model Type: Causal Language Model
Base Model: BioMistral-7B
Language: French (adapted from English medical model)
Dataset: NACHOS corpus (opeN crAwled frenCh Healthcare cOrpuS)
Size: 7.4 GB of French medical texts
Word Count: Over 1 billion words
Sources: 24 French medical websites
Training Duration: 2.8 epochs
Hardware: 32 NVIDIA H100 80GB GPUs
Training Time: 11 hours
Optimizer: AdamW
Learning Rate: 2e-5
Weight Decay: 0.01
Batch Size: 16 with gradient accumulation of 2
Supervised Fine-Tuning (SFT)
Dataset: 30K French medical question-answer pairs
10K native French medical questions
10K translated medical questions from English resources
10K generated questions from French medical texts
Method: DoRA (Weight-Decomposed Low-Rank Adaptation)
Training Duration: 10 epochs
Hardware: 1 NVIDIA H100 80GB GPU
Training Time: 42 hours
Rank: 16
Alpha: 16
Learning Rate: 2e-5
Batch Size: 4
Computational Impact
Total Training Time: 53 hours (11h CPT + 42h SFT)
Hardware: 32 GPU H100 + 1 GPU H100
Carbon Emissions: 10.11 kgCO2e (9.04 + 1.07)
Ethical Considerations
Medical Accuracy: This model is for research and educational purposes only. Performance limitations make it unsuitable for critical medical applications
Bias: May contain biases from both English and French medical literature
