
# Dataset from the paper [Debiasing Pre-Trained Language Models via Efficient Fine-Tuning](https://aclanthology.org/2022.ltedi-1.8/)
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The dataset is formed by combining two different datasets: [WinoBias](https://github.com/uclanlp/corefBias) and [CrowS-Pairs](https://github.com/nyu-mll/crows-pairs) 
license:mit region:us
{"license": "mit"}
TAGS
#license-mit #region-us 


# Dataset from the paper Debiasing Pre-Trained Language Models via Efficient Fine-Tuning
------------------------
The dataset is formed by combining two different datasets: WinoBias and CrowS-Pairs 
# Dataset from the paper Debiasing Pre-Trained Language Models via Efficient Fine-Tuning
------------------------
The dataset is formed by combining two different datasets: WinoBias and CrowS-Pairs
TAGS
#license-mit #region-us 
 # Dataset from the paper Debiasing Pre-Trained Language Models via Efficient Fine-Tuning
------------------------
The dataset is formed by combining two different datasets: WinoBias and CrowS-Pairs
passage: TAGS
#license-mit #region-us 
# Dataset from the paper Debiasing Pre-Trained Language Models via Efficient Fine-Tuning
------------------------
The dataset is formed by combining two different datasets: WinoBias and CrowS-Pairs