π§π· pt-ai-detector-sent
Sentence-level Portuguese classifier that flags whether a single sentence was likely written by a Large-Language-Model (LLM) or by a human.
Why? The document-level model Detecting-ai/pt-ai-detector
works great on paragraphs, but very short inputs lost accuracy.
This checkpoint inherits that backbone and is fine-tuned on 200 k balanced sentences.
property | value |
---|---|
Base checkpoint | Detecting-ai/pt-ai-detector |
Fine-tune data | 100 000 human + 100 000 AI sentences (β₯ 4 words) |
LLMs used for AI text | Azure OpenAI gpt-4o-mini, gpt-4o, gpt-35-turbo |
Training | 1 epoch Β· batch 16 Β· lr 1 e-5 Β· A100-40 GB |
Validation F1 | 0.989 (balanced sentences) |
Intended use | quick checks inside larger pipelines, sentence-by-sentence highlighting |
Demo : see the free web checker at detecting-ai.com β powered by this model.
β¨ Quick start
from transformers import pipeline
clf = pipeline(
"text-classification",
model="Detecting-ai/pt-ai-detector-sent",
tokenizer="Detecting-ai/pt-ai-detector-sent",
device_map="auto" # GPU if available
)
txt = "A inteligΓͺncia artificial estΓ‘ transformando a educaΓ§Γ£o."
print(clf(txt, top_k=None))
# β [{'label': 'LABEL_1', 'score': 0.87}] # 1 = AI, 0 = Human
π§ Recommended threshold
score range | interpretation |
---|---|
> 0.70 | likely AI (LLM-generated / paraphrased) |
0.30 β 0.70 | uncertain β review in context |
< 0.30 | likely Human |
For full documents, classify every sentence and aggregate (e.g. βflag as AI if β₯ 30 % of sentences score > 0.70β).
ποΈ Training data
corpus | purpose |
---|---|
wiki40b-pt, oscar-pt, cc100-pt, europarl-pt, opus-books-pt | human prose (web, books, parliament) |
Detecting-ai/ai_pt_corpus | 1 M AI sentences generated with Azure OpenAI models (news, essays, chat, tweets, dialogs, code comments) |
All human corpora were cleaned (language-ID filter, deduplication, URL removal).
Sentences shorter than 4 tokens were dropped.
π Validation metrics
split | precision | recall | F1 |
---|---|---|---|
Human | 0.987 | 0.990 | 0.989 |
AI | 0.991 | 0.988 | 0.989 |
Macro | 0.989 | 0.989 | 0.989 |
Evaluated on a held-out, balanced set of 20 k sentences.
β οΈ Limitations & caveats
- Best on Portuguese sentences β₯ 8β10 tokens; very short fragments are mostly noise.
- Trained on mainstream GPT family (GPT-4o, GPT-35-turbo); accuracy may drop on entirely novel models or heavy prompt-engineering.
- Occasional false-positives on very formal human writing; false-negatives on heavy slang AI output.
- Not a plagiarism detector and does not guarantee authorship.
π License
Creative Commons CC-BY-NC 4.0 β free for research & non-commercial use.
Commercial use requires written permission from the authors.
π€ Team & contact
Built with β€οΈ by the team behind detecting-ai.com.
Questions, issues, partnership requests β support@detecting-ai.com
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Model tree for Detecting-ai/pt-ai-detector-sent
Base model
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