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[Journal de bord Maeumjigi Capstone #13] Limites du 70B & Pivot vers des modèles de taille intermédiaire (HCX, Qwen)

· 3 minutes de lecture
Jaybee
AI & Robotics Engineer

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After experiencing the OOM (Out of Memory) hell during the fine-tuning of massive 70B models, on May 4th, we attempted a bold change in strategy. By drastically reducing the batch size, we barely managed to push the 70B models (Llama3.3, DeepSeek-R1) to checkpoint-1200 and 1300, but the training time was absurdly long, resulting in terrible efficiency.