63 lines
1.7 KiB
Markdown
63 lines
1.7 KiB
Markdown
---
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license: mit
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- debugging
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- tool-use
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- multi-turn
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- reinforcement-learning
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- grpo
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datasets:
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- custom
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language:
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- en
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pipeline_tag: text-generation
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---
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# DSL Debug 7B — RL-Only Step 30
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Qwen2.5-7B-Instruct trained with GRPO (Group Relative Policy Optimization) directly from the base model, no SFT warmup.
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**Blog post:** [Multi-Turn RL for Code Debugging](https://andrewlngdn.github.io/dsl_debugger/)
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**Code + environment:** [github.com/AndrewLngdn/dsl-debug](https://github.com/AndrewLngdn/dsl-debug)
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## Training
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- **Method**: GRPO with multi-turn tool use (verl 0.7 + sglang 0.5.6)
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- **Base model**: Qwen2.5-7B-Instruct (no SFT warmup)
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- **Steps**: 30 (batch size 512, 8 rollouts per prompt)
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- **LR**: 1e-5 cosine
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- **Reward**: Binary (1.0 if submitted code matches expected output, 0.0 otherwise)
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- **Hardware**: 2x A100-SXM4-80GB
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## Results (held-out test, one-shot)
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| Split | Base Model | This Model |
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|-------|:---:|:---:|
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| Standard (481) | 50.5% | **78.8%** |
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| Nonlocal (200) | 12.0% | **54.0%** |
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| Intent-Mismatch (177) | 0.6% | **14.7%** |
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## Alignment Tax
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| Benchmark | Base | This Model |
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|-----------|:---:|:---:|
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| MMLU (5-shot) | 74.6% | 74.7% |
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| GSM8K (8-shot) | 84.9% | 84.4% |
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| HumanEval (0-shot) | 65.9% | 59.1% |
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## Usage
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```python
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from huggingface_hub import snapshot_download
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snapshot_download("andrewlngdn/dsl-debug-7b-rl-only-step30",
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local_dir="/workspace/models/rl_only_step30")
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```
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## Related Models
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| Model | Repo |
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|-------|------|
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| **SFT then RL step 35 (best)** | [andrewlngdn/dsl-debug-7b-sft-rl](https://huggingface.co/andrewlngdn/dsl-debug-7b-sft-rl) |
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| SFT step 100 | [andrewlngdn/dsl-debug-7b-sft-step100](https://huggingface.co/andrewlngdn/dsl-debug-7b-sft-step100) |
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