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--- |
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dataset_info: |
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features: |
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- name: anchor |
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dtype: string |
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- name: positive |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 897778 |
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num_examples: 580 |
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- name: test |
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num_bytes: 532533 |
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num_examples: 339 |
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- name: validation |
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num_bytes: 524735 |
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num_examples: 339 |
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download_size: 875915 |
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dataset_size: 1955046 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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- split: validation |
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path: data/validation-* |
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--- |
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# Dataset Card for Scifact-TR |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Fields](#data-fields) |
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- [Source Data](#source-data) |
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## Dataset Description |
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Scifact-TR is originally [released](https://huggingface.co/datasets/trmteb/scifact-tr_fine_tuning_dataset) by [TR-MTEB](https://huggingface.co/trmteb) group. |
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### Dataset Structure |
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The original dataset only had `train` and `test` split. We applied the following splitting methodology to obtain the `validation` split: |
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* If a train-val-test split is available, we use the existing divisions as provided. |
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* 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. |
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* 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. |
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* In cases with a val-test split, we split validation into train and vad sets in 80\% and 20\% proportions, respectively. |
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* 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. |
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### Data Fields |
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- **anchor** (string): A user query in Turkish. |
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- **positive** (string): A factual answer in Turkish related to the anchor. |
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## Source Dataset |
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[hf.co/trmteb/scifact-tr_fine_tuning_dataset](https://huggingface.co/datasets/trmteb/scifact-tr_fine_tuning_dataset) |