MBPP for code RL, deduplicated against MBPP+ (320 train / 378 MBPP+ / 276 heldout)

README.md

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+---
+license: cc-by-4.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- code
+- rlvr
+- reinforcement-learning
+- mbpp
+- verl
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train.parquet
+  - split: test
+    path: data/test.parquet
+  - split: heldout_mbpp_test
+    path: data/heldout_mbpp_test.parquet
+---
+
+# MBPP for code RL (deduplicated against MBPP+)
+
+MBPP prepared for RLVR training in [verl](https://github.com/volcengine/verl),
+with **two independent hold-outs** so both MBPP+ and MBPP's own canonical test
+split stay reportable after training on this data.
+
+| split | rows | contents |
+|---|---|---|
+| `train` | 320 | MBPP canonical train + validation + prompt, minus everything in MBPP+ |
+| `test` | 378 | exactly the problems in [`evalplus/mbppplus`](https://huggingface.co/datasets/evalplus/mbppplus) |
+| `heldout_mbpp_test` | 276 | MBPP's canonical test split (task_id 11-510) that is *not* in MBPP+ |
+
+## Why 320 and not 974
+
+MBPP `full` is 974 problems across four canonical splits (prompt 10, test 500,
+validation 90, train 374). Two things are removed from the training pool:
+
+1. **Everything in MBPP+** (378 problems). MBPP+ is derived from MBPP-sanitized
+   and consumes 378 of that config's 427 problems.
+2. **MBPP's canonical test split.** Deduplicating against MBPP+ alone would
+   leave 596 training problems, but 276 of those are canonical MBPP test — fine
+   if MBPP+ is your only benchmark, fatal if you ever want standard MBPP numbers.
+
+Deduplicating MBPP-**sanitized** against MBPP+ leaves only **49** problems,
+which is why the sanitized config alone is not viable for training. Each problem
+here uses its *sanitized* text and corrected tests where one exists (427 of 974
+do) while keeping the other 547 — sanitized quality at usable size.
+
+Leakage is asserted at build time: no train `task_id` appears in MBPP+, and no
+train row comes from a withheld split.
+
+## Format
+
+verl RLHF layout: `data_source`, `prompt`, `ability`, `reward_model`, `extra_info`.
+
+`reward_model.ground_truth` is a **JSON string**:
+
+```json
+{"assert_case": ["assert floor_Min(10,20,30) == 15", "..."]}
+```
+
+The verifier dispatches on the *keys* of that dict, so one reward path handles
+MBPP asserts and competitive-programming stdin/stdout with no dataset-specific
+routing. Setup imports (`test_setup_code` / `test_imports`) are folded into each
+assert string, because every test runs as a standalone script:
+`solution + "\n" + assert_case[i]`.
+
+The prompt is a two-turn chat whose system message matches the math/kk runs of
+the same study, so prompt format is not a confound across tasks:
+
+```
+system: Please reason step by step and put your final solution in a single ```python code block.
+user:   <task> + half the tests as an interface hint + fenced-block instruction
+```
+
+Half the tests (`floor(N/2)`) are shown so the model can infer the function name
+and signature; **all** tests are used for reward.
+
+## Validation
+
+All 974 MBPP reference solutions score 1.0 through the verifier.
+
+## Sources
+
+- [`google-research-datasets/mbpp`](https://huggingface.co/datasets/google-research-datasets/mbpp) (configs `full` and `sanitized`)
+- [`evalplus/mbppplus`](https://huggingface.co/datasets/evalplus/mbppplus)

data/heldout_mbpp_test.parquet

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+size 62264

data/test.parquet

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+size 82958

data/train.parquet

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