Scifact-TR / README.md
ebrarkiziloglu's picture
Update README.md
35c8222 verified
---
dataset_info:
features:
- name: anchor
dtype: string
- name: positive
dtype: string
splits:
- name: train
num_bytes: 897778
num_examples: 580
- name: test
num_bytes: 532533
num_examples: 339
- name: validation
num_bytes: 524735
num_examples: 339
download_size: 875915
dataset_size: 1955046
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
---
# Dataset Card for Scifact-TR
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Source Data](#source-data)
## Dataset Description
Scifact-TR is originally [released](https://huggingface.co/datasets/trmteb/scifact-tr_fine_tuning_dataset) by [TR-MTEB](https://huggingface.co/trmteb) group.
### Dataset Structure
The original dataset only had `train` and `test` split. We applied the following splitting methodology to obtain the `validation` split:
* If a train-val-test split is available, we use the existing divisions as provided.
* For datasets with a train-test split only, we create a val split from the training set, sized to match the test set, and apply this across all models.
* In cases with a train-val split, we reassign the val set as the test split, then generate a new val split from the training data following the approach above.
* In cases with a val-test split, we split validation into train and vad sets in 80\% and 20\% proportions, respectively.
* When only a single combined split is present, we partition the data into train, val, and test sets in 70\%, 15\%, and 15\% proportions, respectively.
### Data Fields
- **anchor** (string): A user query in Turkish.
- **positive** (string): A factual answer in Turkish related to the anchor.
## Source Dataset
[hf.co/trmteb/scifact-tr_fine_tuning_dataset](https://huggingface.co/datasets/trmteb/scifact-tr_fine_tuning_dataset)