martin-ha/toxic-comment-model简介

Model description

This model is a fine-tuned version of the DistilBERT model to classify toxic comments.

How to use

You can use the model with the following code.
from transformers import AutoModelForSequenceClassification, AutoTokenizer, TextClassificationPipeline
model_path = "martin-ha/toxic-comment-model"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSequenceClassification.from_pretrained(model_path)
pipeline = TextClassificationPipeline(model=model, tokenizer=tokenizer)
print(pipeline('This is a test text.'))


Limitations and Bias

This model is intended to use for classify toxic online classifications. However, one limitation of the model is that it performs poorly for some comments that mention a specific identity subgroup, like Muslim. The following table shows a evaluation score for different identity group. You can learn the specific meaning of this metrics here. But basically, those metrics shows how well a model performs for a specific group. The larger the number, the better.

subgroup subgroup_size subgroup_auc bpsn_auc bnsp_auc muslim 108 0.689 0.811 0.88 jewish 40 0.749 0.86 0.825 homosexual_gay_or_lesbian 56 0.795 0.706 0.972 black 84 0.866 0.758 0.975 white 112 0.876 0.784 0.97 female 306 0.898 0.887 0.948 christian 231 0.904 0.917 0.93 male 225 0.922 0.862 0.967 psychiatric_or_mental_illness 26 0.924 0.907 0.95