|
--- |
|
dataset_info: |
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features: |
|
- 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: 17791088 |
|
num_examples: 50000 |
|
download_size: 11682866 |
|
dataset_size: 17791088 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
--- |
|
# MTEB Toxic Conversations 50k Triplets Dataset |
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|
|
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. |
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|
|
|
|
## 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} |
|
} |
|
``` |