ky1916/hatcorpus-bert-authorship

HATCorpus BERT Authorship Classifier

Model Description

This model is a BERT-based binary text classifier trained to distinguish between human-written and AI-generated English text.

• —Base model: bert-base-uncased
• —Task: Binary text classification
• —Labels:
• —0 → Human-written
• —1 → AI-generated

The model was trained on HATCorpus, a curated dataset of human and AI-authored text.

Intended Use

This model is intended for:

• —Research on AI-generated text detection
• —Benchmarking authorship classifiers
• —Educational and exploratory use

It is not intended for:

• —Surveillance or enforcement
• —Determining individual authorship
• —High-stakes automated decisions

Training Data

• —Dataset: HATCorpus
• —Sources: Wikipedia, Project Gutenberg, AI-generated text
• —Language: English
• —Split: Train / Validation

For dataset details, see: 👉 https://huggingface.co/datasets/ky1916/HATCorpus

Training Details

• —Architecture: BERT-base
• —Optimizer: AdamW
• —Loss: Cross-entropy
• —Max sequence length: 512
• —Batch size: 8
• —Epochs: 3

Evaluation

(Evaluated against dataset at https://www.kaggle.com/datasets/shanegerami/ai-vs-human-text)

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

tokenizer = AutoTokenizer.from_pretrained("your-username/hatcorpus-bert-authorship")
model = AutoModelForSequenceClassification.from_pretrained("your-username/hatcorpus-bert-authorship")

text = "This is an example sentence."
inputs = tokenizer(text, return_tensors="pt", truncation=True)
outputs = model(**inputs)
prediction = torch.argmax(outputs.logits, dim=1).item()

print("AI-generated" if prediction == 1 else "Human-written")

Limitations

• —Performance may degrade on very short text
• —Model may rely on stylistic cues rather than semantic understanding
• —Does not generalize to all LLMs or writing styles

Citation

If you use this model in your research, please cite both the model and dataset:

@model{hatcorpus_bert_2025,
  title     = {HATCorpus BERT Authorship Classifier},
  year      = {2025},
  publisher = {Hugging Face},
  note      = {Fine-tuned from bert-base-uncased for human vs AI text classification}
}