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Model: laion/explore-tis-minp-40-8B
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: laion/GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink
+tags:
+- rl
+- skyrl
+- terminal-bench
+- agentic
+- tis
+---
+
+# explore-tis-minp-40-8B
+
+RL (SkyRL, agentic terminal-bench / Harbor + Daytona) checkpoint from the `explore-tis` sampling-parameter ablation.
+This is the **min-p sampling** arm (`explore-tis-minp`).
+
+- **Base model:** `laion/GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink` (an 8B model)
+- **Dataset:** `DCAgent/exp_rpt_pymethods2test-large`
+- **Algorithm:** RLOO-n, no KL loss, `loss_reduction=seq_mean_token_sum_norm_global`, TIS on (`tis_imp_ratio_cap=2.0`)
+- **Sampling:** temperature=1.0, min_p=0.05, top_k=-1, top_p=1.0
+- **Selected checkpoint:** `global_step_40` (best trailing-5 EMA, α=1/3, of `reward/avg_raw_reward` over saved exports with step ≤ 78; EMA ≈ 0.4722). The 78-step cutoff was applied to exclude a step-79+ greedy/eval-pass reward artifact.
+- **Max training steps:** 80
+
+## Training Traces
+
+Rollout traces for this run: [penfever/explore-tis-minp](https://huggingface.co/datasets/penfever/explore-tis-minp)
+
+## Training Logs
+
+Parsed metrics, reward-vs-steps plots, and raw console logs are under `training_logs/` in this repo.