| --- |
| language: |
| - ur |
| license: apache-2.0 |
| tags: |
| - text-classification |
| - sentiment-analysis |
| - urdu |
| - bert |
| - fine-tuned |
| - nlp |
| datasets: |
| - mirfan899/imdb_urdu_reviews |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: urdu-sentiment-classifier |
| results: |
| - task: |
| type: text-classification |
| dataset: |
| name: IMDB Urdu Reviews |
| type: mirfan899/imdb_urdu_reviews |
| metrics: |
| - type: accuracy |
| value: 0.81 |
| - type: f1 |
| value: 0.8098 |
| --- |
| |
| # Urdu Sentiment Classifier 🇵🇰 |
|
|
| A fine-tuned **bert-base-multilingual-cased** model for **Urdu sentiment analysis** — classifying Urdu text as positive or negative. |
|
|
| ## Live Demo |
|
|
| [Try it on HuggingFace Spaces](https://huggingface.co/spaces/H-Layba/urdu-sentiment-classifier) |
|
|
| ## Performance |
|
|
| | Metric | Score | |
| |--------|-------| |
| | Accuracy | 81.00% | |
| | F1 Score (weighted) | 0.8098 | |
|
|
| ## Example Predictions |
|
|
| ```python |
| from transformers import pipeline |
| |
| classifier = pipeline("text-classification", model="H-Layba/urdu-sentiment-classifier") |
| |
| classifier("یہ فلم بہت اچھی تھی") |
| # [{'label': 'positive', 'score': 0.9936}] |
| |
| classifier("آج کا دن بہت برا تھا") |
| # [{'label': 'negative', 'score': 0.9918}] |
| ``` |
|
|
| ## Training Details |
|
|
| - **Base model:** bert-base-multilingual-cased |
| - **Dataset:** 50,000 Urdu movie reviews |
| - **Epochs:** 5 |
| - **Learning rate:** 2e-5 |
| - **Batch size:** 32 (train), 64 (eval) |
| - **Hardware:** Kaggle T4 GPU |
| - **Mixed precision:** fp16 |
|
|
| ## Dataset |
|
|
| Trained on `mirfan899/imdb_urdu_reviews` — 50,000 Urdu translations of IMDB movie reviews with positive/negative sentiment labels. |
|
|
| ## Part of Urdu NLP Suite |
|
|
| This model is part of a larger collection of fine-tuned Urdu NLP models: |
| - [x] Sentiment Classification ← this model |
| - [ ] Text Summarization |
| - [ ] Question Answering |
| - [ ] Urdu → English Translation |
