license, base_model, tags, datasets, language, pipeline_tag
| license |
base_model |
tags |
datasets |
language |
pipeline_tag |
| mit |
Qwen/Qwen2.5-7B-Instruct |
| debugging |
| tool-use |
| multi-turn |
| sft |
|
|
|
text-generation |
DSL Debug 7B — SFT Step 100
Qwen2.5-7B-Instruct fine-tuned on 1,593 debugging trajectories for the DSL Debug environment.
Blog post: Multi-Turn RL for Code Debugging
Code + environment: github.com/AndrewLngdn/dsl-debug
Training
- Method: Supervised fine-tuning (verl 0.7)
- Data: 1,593 multi-turn trajectories with tool calls (run, inspect, read_docs, submit)
- Base model: Qwen2.5-7B-Instruct
- Epochs: 2 (step 100 checkpoint)
- LR: 5e-6
- Hardware: 2x A100-SXM4-80GB
Results (held-out test, one-shot)
| Split |
Base Model |
This Model |
| Standard (481) |
50.5% |
56.3% |
| Nonlocal (200) |
12.0% |
40.0% |
| Intent-Mismatch (177) |
0.6% |
7.9% |
Alignment Tax
| Benchmark |
Base |
This Model |
| MMLU (5-shot) |
74.6% |
74.6% |
| GSM8K (8-shot) |
84.9% |
83.9% |
| HumanEval (0-shot) |
65.9% |
62.2% |
Usage
This checkpoint is primarily used as the starting point for SFT then RL training (GRPO), which achieves the best results.
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