RedditBias

Data Preparation

The data preparation code is included in the directory - DataPreparation

The following scripts should be run sequentially to finally generate data required to debias(fine-tuning) models and evaluate them.

• DataPreparation/reddit_data.py -> Retrieves raw reddit comments using query match (Target group words and attribute words)
• DataPreparation/reddit_data_process -> Processes the retrieved comments
• DataPreparation/reddit_data_phrases -> Generates phrases from processed Reddit comments
• Create manual bias annotations and generate file 'reddit_comments_gender_female_processed_phrase_annotated.csv'
• DataPreparation/reddit_data_phrases_replace_target.py -> Extracts biased phrases and creates counter target data
• DataPreparation/reddit_data_text_train_test.py -> Creates train test split of biased phrases
• evaluation/measure_bias.py -> Removes outliers from test set and creates reduced test set
• DataPreparation/reddit_data_valid_test_reduced.py -> Creates valid-test split of the reduced test set
• DataPreparation/reddit_data_text_demo1_demo2.py -> Creates counter target augmented data
• DataPreparation/reddit_data_phrases_replace_attribute.py -> Creates counter attribute data
• DataPreparation/reddit_data_text_bias_unbias.py -> Creates test files of counter attribute augmented data

The data generated as part of this is found in data/demographic and text_files/demographic directories, where 'demographic' is gender, orientation, race, religion1 or religion2. The txt files in folder text_files/ are used for train, validation and evaluation during fine-tuning the DialoGPT model using Debiasing methods.

A brief description of files in data/religion1 is:

• religion2_muslims.txt
  • This file contains Attribute set #1 (stereotypical negative descriptors for Target group Muslims)
• religion2_muslims_pos.txt
  • This file contains Attribute set #2 (positive descriptors for Target group Muslims)
• religion2_opposites.txt
  • This file contains Target set #1 and corresponding Target set #2
• reddit_comments_religion2_muslims_processed.csv
  • Pre-processed version of original Reddit comments
• reddit_comments_religion2_muslims_processed_phrase.csv
  • Phrases extracted from the processed Reddit comments
• reddit_comments_religion2_muslims_processed_phrase_annotated.csv
  • Manual bias annotations for Reddit comments and phrases
• reddit_comments_religion2_christians_biased_test_reduced.csv and reddit_comments_religion2_muslims_biased_test_reduced.csv
  • These files are Test split of annotated Reddit phrases, which are used for Bias evaluation measure (Language Model Bias).
• reddit_comments_religion2_christians_biased_valid_reduced.csv and reddit_comments_religion2_muslims_biased_valid_reduced.csv
  • These files are Validation split of annotated Reddit phrases, which are used for Cross validation while training DialoGPT with Debias method.
• reddit_comments_religion2_muslims_processed_phrase_biased_testset_neg_attr_reduced.csv and reddit_comments_religion2_muslims_processed_phrase_biased_testset_pos_attr_reduced.csv
  • These files are test split of Reddit phrases used for Bias evaluation over contrasting Attributes for marginalised demographic.

Note: The unprocessed reddit comment files could not be uploaded to GitHub due to size constraints. Find it on https://drive.google.com/drive/folders/1FC79WZyuVJRGXf4OzGoX4z84wvwhBxgh?usp=sharing

Language Model Bias (Significance test Bias evaluation)

• Evaluation/measure_bias.py

  • This script performs Student t-test on the perplexity distribution of two sentences groups with contrasting targets. For example works on files: reddit_comments_religion2_christians_biased_test_reduced.csv and reddit_comments_religion2_muslims_biased_test_reduced.csv. Set variable 'REDUCE_SET' to remove outliers from target set. Unset variable ''REDUCE_SET' if you are already using reduced test set for input

• Evaluation/measure_bias_attribute_swap.py

  • This script performs Student t-test on the perplexity distribution of two sentences groups with contrasting attributes. For example works on files: reddit_comments_religion2_muslims_processed_phrase_unbiased_testset_pos_attr_reduced.csv and reddit_comments_religion2_muslims_processed_phrase_biased_testset_neg_attr_reduced.csv. Set variable 'REDUCE_SET' to remove outliers from target set. Unset variable ''REDUCE_SET' if you are already using reduced test set for input

Generate response from models

• Decoding/generate.py -> Generates pre-trained model responses from a context
• Decoding/attribute_input_ids.py -> Creates token ids of attribute words
• Decoding/target_input_ids.py -> Creates token ids of target words

Debiasing code and Performance in Conversational tasks

Find the code for Algorithm level and Data level debiasing and evaluation (Dialog State Tracking & Response Generation) of debiased model in forked repo: https://github.com/SoumyaBarikeri/debias_transformers