Datasets:
File size: 1,395 Bytes
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license: cc-by-4.0
tags:
- chemistry
- molecule-optimization
configs:
- config_name: ind
data_files:
- split: train
path: ind/train.parquet
- split: test
path: ind/test.parquet
- config_name: ood
data_files:
- split: train
path: ood/train.parquet
- split: test
path: ood/test.parquet
- config_name: all
data_files:
- split: train
path:
- ind/train.parquet
- ood/train.parquet
- split: test
path:
- ind/test.parquet
- ood/test.parquet
---
# MuMOInstruct, hub-native
`NingLab/MuMOInstruct` (`f3ca492caaca6ecb33b1fcff65d882f10acc3297`), restricted to the paper's own IND/OOD evaluation split (the ten declared property combinations) and restructured into `ind`/`ood` subsets, with the unified columns `id`, `query`, `ground_truth`, `response`, `subtask` and `scoring_context` added beside every original one. `ground_truth` is the train split's own `target_smiles` and `response` its tagged form; both are blank for every test row, which upstream carries no target for -- the oracle scores the one candidate's property change against the source molecule, not a stored answer. See `scripts/datasets/README.md` in the AutoDataSci repository for what those columns mean.
Row counts: {"train": 19841, "test": 7810}.
```json
{
"ind": {
"train": 14804,
"test": 5000
},
"ood": {
"train": 5037,
"test": 2810
}
}
```
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