|
--- |
|
dataset_info: |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: label |
|
dtype: |
|
class_label: |
|
names: |
|
'0': datetime_query |
|
'1': iot_hue_lightchange |
|
'2': transport_ticket |
|
'3': takeaway_query |
|
'4': qa_stock |
|
'5': general_greet |
|
'6': recommendation_events |
|
'7': music_dislikeness |
|
'8': iot_wemo_off |
|
'9': cooking_recipe |
|
'10': qa_currency |
|
'11': transport_traffic |
|
'12': general_quirky |
|
'13': weather_query |
|
'14': audio_volume_up |
|
'15': email_addcontact |
|
'16': takeaway_order |
|
'17': email_querycontact |
|
'18': iot_hue_lightup |
|
'19': recommendation_locations |
|
'20': play_audiobook |
|
'21': lists_createoradd |
|
'22': news_query |
|
'23': alarm_query |
|
'24': iot_wemo_on |
|
'25': general_joke |
|
'26': qa_definition |
|
'27': social_query |
|
'28': music_settings |
|
'29': audio_volume_other |
|
'30': calendar_remove |
|
'31': iot_hue_lightdim |
|
'32': calendar_query |
|
'33': email_sendemail |
|
'34': iot_cleaning |
|
'35': audio_volume_down |
|
'36': play_radio |
|
'37': cooking_query |
|
'38': datetime_convert |
|
'39': qa_maths |
|
'40': iot_hue_lightoff |
|
'41': iot_hue_lighton |
|
'42': transport_query |
|
'43': music_likeness |
|
'44': email_query |
|
'45': play_music |
|
'46': audio_volume_mute |
|
'47': social_post |
|
'48': alarm_set |
|
'49': qa_factoid |
|
'50': calendar_set |
|
'51': play_game |
|
'52': alarm_remove |
|
'53': lists_remove |
|
'54': transport_taxi |
|
'55': recommendation_movies |
|
'56': iot_coffee |
|
'57': music_query |
|
'58': play_podcasts |
|
'59': lists_query |
|
- name: label_text |
|
dtype: string |
|
- name: 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: 1202479 |
|
num_examples: 11514 |
|
download_size: 658224 |
|
dataset_size: 1202479 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
--- |
|
# MTEB Amazon Massive Intent 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} |
|
} |
|
``` |
