---
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)