JustRL: Simplicity at Scale 🚀 Competitive RL Performance Without Complex Techniques 🌟 JustRL demonstrates that competitive reinforcement learning performance for small language models doesn’t require complex multi-stage pipelines or dynamic schedules. Using a minimal recipe with single-stage training and fixed hyperparameters, we achieve state-of-the-art results on mathematical reasoning tasks. We release two models: — JustRL-DeepSeek-1.5B: Trained from DeepSeek-R1-Distill-Qwen-1.5B — JustRL-Nemotron-1.5B: Trained from OpenMath-Nemotron-1.5B Both models use identical hyperparameters without per-model tuning, demonstrating the robustness of our approach. !The AIME24 performance curve for scaling from a weak base DeekSeek-R1-Distill-Qwen-1.5B and a strong base OpenMath-Nemotron-1.5B over thousands of steps. ✨ Simplicity: Single-stage training with fixed hyperparameters, without multi-stage pipelines or dynamic schedules 📈 Stability: Smooth, monotonic improvement over 4,000+ training steps without collapses or oscillations 🎯 Performance: State-of-the-art results at 1.5B scale, matching or exceeding more complex approaches 💰 Efficiency: Comparable or better performance with 2× less…
Модальности:
Генерация текста
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Диалог / чат
Задача: Генерация текста
Автор: hbx
Теги: qwen2, conversational, en, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 111
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
