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Model: andrewlngdn/dsl-debug-7b-sft-rl
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---
license: mit
language:
- en
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- reinforcement-learning
- grpo
- tool-use
- debugging
- dsl
datasets:
- custom
pipeline_tag: text-generation
model-index:
- name: dsl-debug-7b-sft-rl
results:
- task:
type: text-generation
name: DSL Debugging (Standard)
metrics:
- type: accuracy
value: 86.1
name: Standard Bugs (481)
- task:
type: text-generation
name: DSL Debugging (Nonlocal)
metrics:
- type: accuracy
value: 70.5
name: Nonlocal Bugs (200)
- task:
type: text-generation
name: DSL Debugging (Intent-Mismatch)
metrics:
- type: accuracy
value: 28.2
name: Intent-Mismatch Bugs (177)
---
# DSL Debug 7B: SFT then RL (Best Checkpoint)
Qwen2.5-7B-Instruct fine-tuned with SFT then GRPO reinforcement learning to debug programs in a custom dataflow DSL. This is the best-performing checkpoint (step 35 of 40 RL steps).
**Blog post:** [Multi-Turn RL for Code Debugging](https://andrewlngdn.github.io/dsl_debugger/)
**Code + environment:** [github.com/AndrewLngdn/dsl-debug](https://github.com/AndrewLngdn/dsl-debug)
## Results
Held-out test set, one-shot evaluation:
| Method | Standard (481) | Nonlocal (200) | Intent-Mismatch (177) |
|--------|:-:|:-:|:-:|
| Prompt Engineering (base) | 50.5% | 12.0% | 0.6% |
| SFT (step 100) | 56.3% | 40.0% | 7.9% |
| RL-only (step 30) | 78.8% | 54.0% | 14.7% |
| **SFT then RL (this model)** | **86.1%** | **70.5%** | **28.2%** |
### Alignment Tax
| Benchmark | Base | This Model |
|-----------|------|-----------|
| MMLU (5-shot) | 74.6% | 74.5% |
| GSM8K (8-shot) | 84.9% | 84.1% |
| HumanEval (0-shot) | 65.9% | 62.2% |
## Training
Two-stage training on 2x A100-80GB using [verl](https://github.com/volcengine/verl) 0.7:
1. **SFT**: 1,593 expert trajectories from GPT-5-mini, full parameter updates, LR=5e-6, 2 epochs (step 100)
2. **GRPO**: 6,420 RL problems, LR=1e-5 cosine, batch 512 prompts x 8 rollouts, 40 steps, no KL penalty
## The Task
The model debugs programs in a custom pipe-based dataflow DSL. Each episode provides buggy code and expected output. The model has 8 turns and 4 tools:
- `run(code)`: Execute DSL code
- `inspect(node_name)`: View intermediate table output
- `read_docs(operation)`: Read DSL documentation
- `submit(code)`: Submit fix (ends episode, binary reward)
## Usage
```python
# With sglang
from sglang import RuntimeEndpoint
import sglang as sgl
runtime = RuntimeEndpoint("http://localhost:30000")
# Or download and serve
from huggingface_hub import snapshot_download
snapshot_download("andrewlngdn/dsl-debug-7b-sft-rl", local_dir="./model")
```
```bash
# Using the dsl-debug CLI
pip install dsl-debug
dsl-debug sglang # downloads and serves this model
dsl-debug eval --split standard # evaluate on test set
```
## Related Models
| Model | Repo |
|-------|------|
| SFT step 100 | [andrewlngdn/dsl-debug-7b-sft-step100](https://huggingface.co/andrewlngdn/dsl-debug-7b-sft-step100) |
| RL-only step 30 | [andrewlngdn/dsl-debug-7b-rl-only-step30](https://huggingface.co/andrewlngdn/dsl-debug-7b-rl-only-step30) |

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{%- if tools %}
{{- '<|im_start|>system\n' }}
{%- if messages[0]['role'] == 'system' %}
{{- messages[0]['content'] }}
{%- else %}
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
{%- endif %}
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
{%- else %}
{%- if messages[0]['role'] == 'system' %}
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
{%- else %}
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- for message in messages %}
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- if message.content %}
{{- '\n' + message.content }}
{%- endif %}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '\n<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{{- tool_call.arguments | tojson }}
{{- '}\n</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- message.content }}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
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