size_categories:100K<n<1M format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: question
    dtype: string
  - name: label
    dtype: int64
  - name: passage
    dtype: string
  splits:
  - name: train
    num_bytes: 51552735.34737127
    num_examples: 393631
  download_size: 20127316
  dataset_size: 51552735.34737127
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Dataset Card for "snli_boolq_train"
### This dataset contains validation and training data from both boolq and snli

## snli_boolq_train is a mixed dataset containing both boolq (https://huggingface.co/datasets/boolq) and the "entail" and "contradict" samples from snli (https://huggingface.co/datasets/snli). The selection of this data was to increase the finetuning dataset amount for large language models with uninitialized weights. neutral statements were removed to ensure the compatibility of the two datasets. The original boolq paper demonstrated that minimal loss to boolq accuracy could be achieved by removing neutral statements from the snli dataset (https://aclanthology.org/N19-1300.pdf)