README.md

---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: label
    dtype: int64
  - name: label_text
    dtype: string
  - name: idx
    dtype: int64
  - name: query_idx
    dtype: int64
  - name: positive_idx
    dtype: int64
  - name: negative_idx
    dtype: int64
  splits:
  - name: train
    num_bytes: 3790946
    num_examples: 27481
  download_size: 2513333
  dataset_size: 3790946
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# MTEB Tweet Sentiment Extraction Triplets Dataset

This dataset was used in the paper GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning. Refer to https://arxiv.org/abs/2402.16829 for details.

The code for generating the data is available at https://github.com/avsolatorio/GISTEmbed/blob/main/scripts/create_classification_dataset.py.


## Citation
```
@article{solatorio2024gistembed,
    title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
    author={Aivin V. Solatorio},
    journal={arXiv preprint arXiv:2402.16829},
    year={2024},
    URL={https://arxiv.org/abs/2402.16829}
    eprint={2402.16829},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}
```