| --- |
| license: apache-2.0 |
| base_model: laion/r2egym-nl2bash-stack-bugsseq-fixthink-again |
| tags: |
| - reinforcement-learning |
| - code |
| - pymethods2test |
| - r2egym |
| - rl |
| - rloo-n |
| - terminus-structured |
| language: |
| - en |
| pipeline_tag: text-generation |
| library_name: transformers |
| --- |
| |
| # rl_pymethods2test-r2egym_terminus-structured |
|
|
| RL-trained Qwen3-8B with structured tool calls (terminus-structured agent). |
|
|
| ## Training Pipeline |
|
|
| SFT (r2egym+nl2bash+swesmith) → RL mixed dataset (37 steps) → RL full r2egym (55 steps) → RL pymethods2test (156 steps, full epoch) |
|
|
| ## Key Results |
|
|
| - **SWEBench-100 pass@3**: 37-42% (depending on eval run) |
| - **Pymethods2test pass@8**: 91-97% |
| - **SWEBench in-train eval**: up to 14 fully solved at various checkpoints |
| - Training on test-writing (pymethods) maintains code-editing ability (SWEBench) |
|
|
| ## Training Details |
|
|
| - **Base model**: [laion/r2egym-nl2bash-stack-bugsseq-fixthink-again](https://huggingface.co/laion/r2egym-nl2bash-stack-bugsseq-fixthink-again) |
| - **Agent**: terminus-structured (bash, view, edit, create, search tools) |
| - **Algorithm**: RLOO-N |
| - **Learning rate**: 1e-5 |
| - **Context**: 32k (24k input + 8k output) |
| - **Framework**: BenSkyRL + Harbor (JSC HPC) |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model = AutoModelForCausalLM.from_pretrained("laion/rl_pymethods2test-r2egym_terminus-structured") |
| tokenizer = AutoTokenizer.from_pretrained("laion/rl_pymethods2test-r2egym_terminus-structured") |
| ``` |
|
|
