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--- |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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- name: label |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 17427403 |
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num_examples: 7854 |
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- name: test |
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num_bytes: 3772766 |
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num_examples: 1683 |
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- name: validation |
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num_bytes: 3687534 |
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num_examples: 1683 |
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download_size: 13067873 |
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dataset_size: 24887703 |
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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 Thesis-Abstract-Classification-11K |
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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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Thesis-Abstract-Classification-11K dataset is obtained by processing a subset of [Turkish Academic Theses](https://huggingface.co/datasets/umutertugrul/turkish-academic-theses-dataset) dataset. |
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### Dataset Structure |
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The original dataset was large and examples had several `subject` fields, representing the field of the thesis. |
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In order to construct a single-class classification problem with a reasonable data size, the following steps are carried out: |
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* For each example, only the first value of `subject` field was kept as the main field of the thesis to act as a label. |
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* Data points for a label with less than 60 examples were dropped, which resulted in 187 unique labels. |
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* Random 60 examples for each label is selected to construct a dataset of 11,220 examples. |
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#### Split Methodology |
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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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- **text**(string) : Thesis abstract |
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- **label**(string) : Field of the thesis |
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## Source Dataset |
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[HuggingFace](umutertugrul/turkish-academic-theses-dataset) |
