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license: mit
task_categories:
- text-classification
language:
- en
pretty_name: MPQA
size_categories:
- 10K<n<100K
---
Dataset used in the paper:
A thorough benchmark of automatic text classification
From traditional approaches to large language models
https://github.com/waashk/atcBench
To guarantee the reproducibility of the obtained results, the dataset and its respective CV train-test partitions is available here.
Each dataset contains the following files:
- data.parquet: pandas DataFrame with texts and associated encoded labels for each document.
- split_\<k\>.pkl: pandas DataFrame with k-cross validation partition.
- For each fold \<k\>:
- train_fold_\<k\>.parquet: pandas DataFrame with texts and associated encoded labels for each document on the training split k (according to split_\<k\>.pkl)
- train_fold_\<k\>.parquet: pandas DataFrame with texts and associated encoded labels for each document on the testing split k (according to split_\<k\>.pkl)
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