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BATCH_VALIDATION.md
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# Batch Validation — 5 Cascade-Only Instances
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**Job:** [6a04d3a33308d79117b8f24c](https://huggingface.co/jobs/narcolepticchicken/6a04d3a33308d79117b8f24c)
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**Status:** RUNNING
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**Started:** 2026-05-13
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## Instances
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These are the cascade-only instances from the corrected report — solved by T1 or T2 but NOT by either T4 model:
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1. `django__django-11815`
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2. `django__django-13089`
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3. `django__django-13807`
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4. `django__django-14315` (single-instance test: T2 produced valid 3997ch diff)
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5. `matplotlib__matplotlib-25224`
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## Approach
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- **T1:** Llama-3.1-8B-Instruct (25 turn max)
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- **T2:** Llama-3.3-70B-Instruct (20 turn max)
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- **Protocol:** File editing (`<edit path='file'>content</edit>`) + `git diff` external
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- **Validation:** `git apply --check` on generated patch
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- **Cost:** $0 inference (HF free) + ~$2-3 compute
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## Expected Result
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If the cascade thesis holds, we should see:
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- 3-5 instances producing valid patches
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- Mix of T1 and T2 solves
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- Evidence that cheap models can solve instances that frontier models miss
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## Check Logs
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```bash
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curl -s "https://huggingface.co/api/jobs/narcolepticchicken/6a04d3a33308d79117b8f24c/logs"
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```
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