
A fine-tuned multilingual model for Vietnamese language
📋 Overview
This model serves as a small-scale experiment (0.5B parameters) testing the Reinforcement Learning capabilities of veRL framework. The implementation uses PPO (Proximal Policy Optimization) method on a limited training dataset to evaluate veRL's performance and training behavior.
🔧 Method
The experimentation process was conducted using veRL, focusing on:
- Implementation of PPO algorithm with a 0.5B parameter model
- Running training experiments on a small dataset
- Testing veRL's framework capabilities in handling RL tasks
- Evaluating training efficiency and model behavior
This lightweight approach allowed us to assess veRL's performance in a controlled, small-scale environment.
📊 VLMU Benchmark
EVALUATION DATE | STEM 🔬 | SOCIAL SCIENCE 🌍 | HUMANITIES 📚 | OTHERS 🎯 | AVG ⭐ |
---|---|---|---|---|---|
07/02/2025 | 23.18 | 32.84 | 32.71 | 33.67 | 29.43 |
🤝 Contributors
Developed with ❤️ by BlossomAI
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