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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- en |
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metrics: |
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- f1 |
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- accuracy |
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widget: |
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- text: Girls like attention and they get desperate |
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tags: |
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- sexism |
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datasets: |
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- tum-nlp/sexism-socialmedia-balanced |
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--- |
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# BERTweet for sexism detection |
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This is a fine-tuned BERTweet large ([BERTweet: A pre-trained language model for English Tweets](https://aclanthology.org/2020.emnlp-demos.2/)) model for detecting sexism. |
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The training dataset is **new balanced** version of Explainable Detection of Online Sexism ([**EDOS**](https://github.com/rewire-online/edos))--[sexism-socialmedia-balanced](https://huggingface.co/datasets/tum-nlp/sexism-socialmedia-balanced)--consisting of 16000 entries in |
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English gathered from social media platforms: Twitter and Gab. It achieved a **Macro-F1** score of **0.85** and an **Accuracy** of **0.88** on the test set for the EDOS task. |
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## How to use |
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```python |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline |
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# Load model and tokenizer |
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tokenizer = AutoTokenizer.from_pretrained('tum-nlp/bertweet-sexism') |
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model = AutoModelForSequenceClassification.from_pretrained('tum-nlp/bertweet-sexism') |
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# Create the pipeline for classification |
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sexism_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer) |
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# Predict |
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sexism_classifier("Girls like attention and they get desperate") |
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``` |
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## Licensing Information |
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[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa]. |
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[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa] |
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[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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[cc-by-nc-sa-image]: https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png |
