# Dataset Card for "BIS_Speeches_97_23"

This dataset is built from scrapped speeches on the Bank of International Settlements thanks to this repo : https://github.com/HanssonMagnus/scrape_bis. The dataset is made of 12k speeches from 1997 to 2023.
Each pair is built with extracted sentences from speeches, if B is following A then the 'next_sentence_label' is 1 else it is 0.
Negative pairs are built by choosing a sentence from another speech randomly.)
task_categories:text-classification task_categories:token-classification size_categories:100K<n<1M language:en license:apache-2.0 economics finance business region:us
{"language": ["en"], "license": "apache-2.0", "size_categories": ["100K<n<1M"], "task_categories": ["text-classification", "token-classification"], "dataset_info": {"features": [{"name": "sequenceA", "dtype": "string"}, {"name": "sequenceB", "dtype": "string"}, {"name": "next_sentence_label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 505762257.6721524, "num_examples": 773395}, {"name": "test", "num_bytes": 89252509.32784761, "num_examples": 136482}], "download_size": 365034957, "dataset_size": 595014767}, "tags": ["economics", "finance", "business"]}
TAGS
#task_categories-text-classification #task_categories-token-classification #size_categories-100K<n<1M #language-English #license-apache-2.0 #economics #finance #business #region-us 

# Dataset Card for "BIS_Speeches_97_23"

This dataset is built from scrapped speeches on the Bank of International Settlements thanks to this repo : URL The dataset is made of 12k speeches from 1997 to 2023.
Each pair is built with extracted sentences from speeches, if B is following A then the 'next_sentence_label' is 1 else it is 0.
Negative pairs are built by choosing a sentence from another speech randomly.)
# Dataset Card for "BIS_Speeches_97_23"

This dataset is built from scrapped speeches on the Bank of International Settlements thanks to this repo : URL The dataset is made of 12k speeches from 1997 to 2023.
Each pair is built with extracted sentences from speeches, if B is following A then the 'next_sentence_label' is 1 else it is 0.
Negative pairs are built by choosing a sentence from another speech randomly.)
TAGS
#task_categories-text-classification #task_categories-token-classification #size_categories-100K<n<1M #language-English #license-apache-2.0 #economics #finance #business #region-us 
 # Dataset Card for "BIS_Speeches_97_23"

This dataset is built from scrapped speeches on the Bank of International Settlements thanks to this repo : URL The dataset is made of 12k speeches from 1997 to 2023.
Each pair is built with extracted sentences from speeches, if B is following A then the 'next_sentence_label' is 1 else it is 0.
Negative pairs are built by choosing a sentence from another speech randomly.)
passage: TAGS
#task_categories-text-classification #task_categories-token-classification #size_categories-100K<n<1M #language-English #license-apache-2.0 #economics #finance #business #region-us 
# Dataset Card for "BIS_Speeches_97_23"

This dataset is built from scrapped speeches on the Bank of International Settlements thanks to this repo : URL The dataset is made of 12k speeches from 1997 to 2023.
Each pair is built with extracted sentences from speeches, if B is following A then the 'next_sentence_label' is 1 else it is 0.
Negative pairs are built by choosing a sentence from another speech randomly.)