
# BERTweet for sexism detection

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.
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
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.

## How to use

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained('tum-nlp/bertweet-sexism')
model = AutoModelForSequenceClassification.from_pretrained('tum-nlp/bertweet-sexism')

# Create the pipeline for classification
sexism_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

# Predict
sexism_classifier("Girls like attention and they get desperate")
```

## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png
{"language": ["en"], "license": "cc-by-nc-sa-4.0", "tags": ["sexism"], "datasets": ["tum-nlp/sexism-socialmedia-balanced"], "metrics": ["f1", "accuracy"], "widget": [{"text": "Girls like attention and they get desperate"}]}
transformers pytorch roberta text-classification sexism en dataset:tum-nlp/sexism-socialmedia-balanced license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #sexism #en #dataset-tum-nlp/sexism-socialmedia-balanced #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 


# BERTweet for sexism detection

This is a fine-tuned BERTweet large (BERTweet: A pre-trained language model for English Tweets) model for detecting sexism.
The training dataset is new balanced version of Explainable Detection of Online Sexism (EDOS)--sexism-socialmedia-balanced--consisting of 16000 entries in
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.

## How to use



## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: URL
[cc-by-nc-sa-image]: https://i.URL
# BERTweet for sexism detection

This is a fine-tuned BERTweet large (BERTweet: A pre-trained language model for English Tweets) model for detecting sexism.
The training dataset is new balanced version of Explainable Detection of Online Sexism (EDOS)--sexism-socialmedia-balanced--consisting of 16000 entries in
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. ## How to use ## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: URL
[cc-by-nc-sa-image]: https://i.URL
TAGS
#transformers #pytorch #roberta #text-classification #sexism #en #dataset-tum-nlp/sexism-socialmedia-balanced #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # BERTweet for sexism detection

This is a fine-tuned BERTweet large (BERTweet: A pre-trained language model for English Tweets) model for detecting sexism.
The training dataset is new balanced version of Explainable Detection of Online Sexism (EDOS)--sexism-socialmedia-balanced--consisting of 16000 entries in
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. ## How to use ## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: URL
[cc-by-nc-sa-image]: https://i.URL
TAGS
#transformers #pytorch #roberta #text-classification #sexism #en #dataset-tum-nlp/sexism-socialmedia-balanced #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
# BERTweet for sexism detection

This is a fine-tuned BERTweet large (BERTweet: A pre-trained language model for English Tweets) model for detecting sexism.
The training dataset is new balanced version of Explainable Detection of Online Sexism (EDOS)--sexism-socialmedia-balanced--consisting of 16000 entries in
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.## How to use## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: URL
[cc-by-nc-sa-image]: https://i.URL