Text Classification
Transformers
TensorBoard
Safetensors
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ePeryy/sexist_detection_text_data_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ePeryy/sexist_detection_text_data_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ePeryy/sexist_detection_text_data_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ePeryy/sexist_detection_text_data_v1") model = AutoModelForSequenceClassification.from_pretrained("ePeryy/sexist_detection_text_data_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fine-tuning BERT to identify sexist content in English language texts.
The code on finetuning is available here.
Intended uses & limitations
This finetuned model is valuable to verify whether a text is sexist or not sexist.
Its usage is limited to english language phrases and to its generated context.
The model is inefficient in detecting single or couple of words.
Training results
| Accuracy | Precision | Recall | F-1 score |
|---|---|---|---|
| 0.8809 | 0.8812 | 0.8810 | 0.8811 |
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