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| license: mit |
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| # DeepScaleR-Easy-10k |
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| RL training set of 10,000 DeepScaleR questions that Gemma-3-4B-IT solved **4/4** |
| (temp 1.0, 4 samples, LENIENT math_verify grading), split train 9,500 / val 500. |
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| Creation (seed 42 throughout): |
| 1. Gemma-3-4B-IT generated 4 responses per DeepScaleR question (40,315 rows). |
| 2. **Dedup v2**: questions grouped under max-strength normalization (case, |
| whitespace, prose punctuation, LaTeX formatting); duplicate groups whose gold |
| answers are not all math_verify-equivalent were removed entirely (167 groups / |
| 567 rows — label conflicts); one random copy kept per surviving group |
| -> 38,796 unique questions. Script: `rl-distill-scripts/data/dedup_deepscaler_it_gen.py`. |
| 3. 10,000 sampled uniformly from the lenient 4/4 bucket (10,053 available). |
| 4. 500 sampled uniformly as validation; remaining 9,500 are train. |
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| Files: `*_train.parquet` and `*_val500.parquet` (500 unique held-out questions). |
| For mean@16 validation, replicate the val rows 16x locally (verl samples one |
| response per row). verl format: data_source "math" (routes to the repo's |
| math_verify scorer), prompt = single user message, reward_model.ground_truth, |
| extra_info carries lenient/strict pass counts. |
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| Built by `rl-distill-scripts/data/build_deepscaler_easy_medium.py` in |
| JasonWei05/rl-distill. |
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