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--- |
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license: cc-by-nc-4.0 |
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language: |
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- pt |
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tags: |
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- ai-detection |
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- text-classification |
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- portuguese |
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- bert |
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- transformers |
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base_model: neuralmind/bert-base-portuguese-cased |
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pipeline_tag: text-classification |
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datasets: |
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- wiki40b-pt |
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- oscar-pt |
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- cc100-pt |
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- europarl-pt |
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- opus-books-pt |
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- Detecting-ai/ai_pt_corpus |
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model_type: bert |
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--- |
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# 🇧🇷 pt-ai-detector |
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**pt-ai-detector** is a BERT-base model fine-tuned to decide whether a Portuguese sentence or paragraph was written by a *human* (`label = 0`) or generated by *AI* (`label = 1`). |
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| Metric | Value | |
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| --------------------- | ------------------------------ | |
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| **Train data** | 1 000 000 human + 1 000 000 AI | |
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| **Balanced test set** | 1 954 190 (½ human, ½ AI) | |
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| **Accuracy** | ≈ 99 % | |
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| **F1 (macro)** | ≈ 0.99 | |
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| **Model size** | 434 M parameters (≈ 430 MB) | |
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--- |
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## 📖 Quick usage |
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**Try it live** at [detecting-ai.com](https://detecting-ai.com/pt) – our team at Detecting-ai built this model and demo so you can instantly test any Portuguese text online. |
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```python |
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from transformers import pipeline |
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clf = pipeline( |
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"text-classification", |
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model="Detecting-ai/pt-ai-detector", |
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tokenizer="Detecting-ai/pt-ai-detector", |
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device=0 # set -1 for CPU |
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) |
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text = "A inteligência artificial está transformando a educação." |
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print(clf(text)) # → [{'label': 'AI', 'score': 0.987}] |
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``` |
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| id | label | |
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| -- | ----- | |
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| 0 | Human | |
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| 1 | AI | |
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--- |
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## 🏋️♂️ Training details |
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* **Base model:** `neuralmind/bert-base-portuguese-cased` |
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* **Epochs:** 3 (fp16 on 1 × A100) |
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* **Batch size:** 32 |
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* **Optimizer/LR:** AdamW 2 × 10⁻⁵ |
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* **Loss:** Cross-entropy |
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### Data sources |
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| Corpus | Lines used | Notes | |
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| ------------------------------------------------------------------------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------ | |
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| Human corpus (wiki40b-pt, oscar-pt, cc100-pt, europarl-pt, opus-books-pt) | 1 M sampled | Diverse Portuguese web/news/books | |
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| **AI corpus** (`Detecting-ai/ai_pt_corpus`) | 1 M | Generated with **OpenAI models** (various GPT-4 / GPT-3.5 variants); prompts cover essays, news, tweets, dialogs, paraphrases, T = 0.6–1.0 | |
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Datasets were **balanced 1 : 1** and shuffled before training. |
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--- |
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## 🚦 Intended use |
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Detect AI-generated Portuguese text in essays, articles, chats, support tickets, etc. |
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### Limitations |
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* Not trained on code or non-Portuguese language. |
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* Accuracy may drop on texts < 10 tokens or heavily paraphrased AI. |
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* **Commercial use is disallowed** (CC-BY-NC-4.0). |
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--- |
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## ⚠️ Future work |
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* Evaluate on adversarial paraphrases. |
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* Distill/quantize for edge deployment. |
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* Extend to multilingual detection. |
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--- |
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## 📜 Citation |
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```bibtex |
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@misc{abdurazzoqov2025ptaidetector, |
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title = {pt-ai-detector: Detecting AI-generated Portuguese Text}, |
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author = {Abdulla Abdurazzoqov}, |
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year = {2025}, |
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howpublished = {Hugging Face hub}, |
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url = {https://huggingface.co/Detecting-ai/pt-ai-detector} |
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} |
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``` |
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--- |
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## 💬 License |
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Creative Commons **CC-BY-NC-4.0** — free for research & personal use; commercial use requires written permission. |
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