Gender Prediction from Text ✍️ → 👩🦰👨 This model predicts the likely gender of an anonymous speaker or writer based solely on the content of an English text. It is built upon DeBERTa v3 large and fine tuned on a diverse, multilingual, and multi domain dataset with both formal and informal texts. 📍 Space link : 🔗 Try it out on Hugging Face Spaces 📁 Model repo : 🔗 View on Hugging Face Hub 🧠 Source code : GitHub 📊 Model Summary Base model : microsoft/deberta v3 large Fine tuned on : binary gender classification task ( female vs male ) Best F1 Score : 0.69 on a balanced multi domain test set Max token length : 128 Evaluation Metrics : F1: 0.69 Accuracy: 0.69 Precision: 0.69 Recall: 0.69 📂 Evaluation : View on Notebook 🧾 Datasets Used Dataset Domain Type samzirbo/europarl.en es.gendered Formal speech (Parliament) English czyzi0/luna speech dataset Phone conversations Polish → Translated czyzi0/pwr azon speech dataset Phone conversations Polish → Translated sagteam/author profiling Social posts Russian → Translated kaushalgawri/nptel en tags and gender v0 Spoken transcripts English Blog Authorship Corpus Blog posts English All datasets were normalized, translated if necessary,…
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