README.md

mmlu (filtered)

Filtered version of cais/mmlu.

Source Dataset

• Original HuggingFace path: cais/mmlu
• Disjoint train/val splits: yes
• train split: 1 subset(s) from train split
• val split: 57 subset(s) from test split

Filtering Methodology

Each example in the original dataset was reviewed by an LLM (GPT-OSS-120B) which assessed quality across several dimensions including factual accuracy, formatting consistency, and instructional clarity. Examples that failed review were collected into a blocklist keyed by source name and original row index.

The filtered dataset was produced by:

1. Loading the original dataset from HuggingFace
2. Stamping each row with its original index (__source_orig_idx__) for traceability
3. Removing all rows whose index appears in the blocklist
4. Validating that row counts match expectations exactly
5. Spot-checking a random sample of surviving rows against the original to verify data integrity

Filtering Impact

Split	Original Rows	Removed	Filtered Rows	% Removed
train	99,842	6,928	92,914	6.94%
val	14,042	0	14,042	0.00%

Schema

All original columns are preserved. One column is added:

• __source_orig_idx__: The row's index in the original (unfiltered) dataset. This provides complete lineage back to the source for debugging and future analysis.

Note: The original train split had a nested structure (subsplit_name: "train"). This has been flattened into top-level columns. When updating data_source_configurations.py to point to this repo, remove the subsplit_name field from the train split config.

Provenance

• Blocklist: data/instruct_mix/train/review_results/blocklist_proposed_20260218_232356.jsonl
• Mixture: assistant_core_midtraining
• Generated: 2026-02-20T12:05:03.203204+00:00