36 lines
1.6 KiB
Markdown
36 lines
1.6 KiB
Markdown
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---
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base_model: laion/GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink
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tags:
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- rl
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- skyrl
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- agentic
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- swe
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library_name: transformers
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---
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# ablation-pymethods2test-seqmean-arm0-30-8B
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RL (SkyRL GRPO) checkpoint from the **sequence-mean / RLOO-n (arm0)** ablation of
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the a3-successor study. The policy loss uses `loss_reduction=sequence_mean` with
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the `advantage_estimator=rloo_n` (RLOO-n) estimator, contrasting with the
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token-mean reduction of the a3 series.
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- **Base model:** [laion/GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink](https://huggingface.co/laion/GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink) (a Qwen3-8B SFT)
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- **Training dataset:** [DCAgent/exp_rpt_pymethods2test-large](https://huggingface.co/datasets/DCAgent/exp_rpt_pymethods2test-large)
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- **Checkpoint:** `global_step_30`.
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- **Training:** SkyRL GRPO, `hf_save_interval=5`, 14x GH200 nodes on JSC Jupiter.
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The `rl_config.yaml` in this repo is the exact launch config used for reproducibility.
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This is the step-30 checkpoint of the same run that produced
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[laion/ablation-pymethods2test-seqmean-arm0-15-8B](https://huggingface.co/laion/ablation-pymethods2test-seqmean-arm0-15-8B) (step 15).
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## Training Traces
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Training-time Daytona/Harbor rollouts for this run are uploaded as
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a companion dataset:
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**[penfever/ablation-pymethods2test-seqmean-arm0](https://huggingface.co/datasets/penfever/ablation-pymethods2test-seqmean-arm0)**
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The dataset contains the `last` episode of each trial (per
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`make_and_upload_trace_dataset --episodes last`) — the same rollouts
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the policy was trained on after rollback / truncation.
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