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🧠 `historical-gpt2-finetuned`

Name: historical-gpt2-finetuned
Availability: InStock

✨ Model Summary

A custom fine-tuned version of gpt2 trained on 500 conversational question-answer pairs focused on the Two-Nation Theory, the Pakistan Movement, and key historical figures like Jinnah and Iqbal. This model generates historically-aligned answers in a chatbot-style format, simulating a Q&A assistant.

📌 Model Details

Property	Value
Base Model	GPT-2 (`gpt2`)
Fine-tuned By	Muhammad Yasir (DevSecure)
Language	English (conversational, formal tone)
Dataset Size	500 examples (JSONL format)
Use Case	Conversational history tutor, education, research
Training Loss	`0.1233` (after 3 epochs)
Trained on	Custom `.jsonl` file with Two-Nation Theory Q&A
License	MIT

📚 Dataset Description

The dataset simulates a dialogue between:

Yasir (asking questions)
AI (providing accurate, historical answers)

Example:

{"text": "Yasir: What was the Two-Nation Theory?\nAI: The Two-Nation Theory stated that Muslims and Hindus were two distinct nations with their own customs, religion, and traditions, and therefore Muslims should have a separate homeland.\n"}

Source Materials Used for Data Curation:

Wikipedia: Two-Nation Theory
Books: Jinnah of Pakistan, India Wins Freedom, Iqbal's Speeches
Academic journals and historical PDFs

🎯 Intended Use

✅ Direct Use

Chatbot-style app for history Q&A
Teaching tool for Pakistan studies
Historical assistant for students and researchers
Offline history tutor for smart learning platforms

🚫 Out-of-Scope

Use in political argumentation or manipulation
Interpretation of modern geopolitical conflicts
Multilingual outputs (no Urdu in current version)

⚠️ Risks, Biases, and Limitations

Model reflects curated historical narratives from available sources; potential for bias in interpretation.
May hallucinate or extrapolate when asked questions far beyond the dataset scope.
Not intended for factual legal or political conclusions.

🛠 How to Use (Code Snippet)

python

from transformers import pipeline

generator = pipeline("text-generation", model="jamyasir/historical-gpt2-finetuned")

prompt = "Yasir: What was Gandhi's opinion on the Two-Nation Theory?\nAI:"
response = generator(prompt, max_length=100, do_sample=True, temperature=0.7)[0]['generated_text']
print(response)

📈 Training & Hyperparameters

Config	Value
Epochs	3
Optimizer	AdamW (default)
Max Length	128 tokens
Tokenizer	GPT-2 (`pad_token = eos_token`)
Learning Rate	5e-5
Framework	Hugging Face `Trainer`

✅ Evaluation Examples

Seen Prompt

Prompt: Yasir: Who introduced the Two-Nation Theory?\nAI: Response:

The concept was popularized by Allama Iqbal in 1930 and later advocated by Muhammad Ali Jinnah.

Unseen Prompt

Prompt: Yasir: Why did Jinnah believe Muslims needed a separate homeland?\nAI: Response:

Jinnah believed that due to religious and cultural differences, Muslims needed an independent state to preserve their identity and rights.

🌱 Environmental Impact

Hardware: Local GPU (RTX 3060) / CPU fallback
Training Time: ~5 minutes
Carbon Emissions: Negligible for 500-sample fine-tuning

🧠 Architecture & Objective

Base: GPT-2, decoder-only transformer
Objective: Causal Language Modeling (CLM)
Modified? No architectural changes; fine-tuning only

✍️ Citation

bibtex

@misc{yasir2025twonationgpt2,
  author       = {Muhammad Yasir},
  title        = {GPT-2 Fine-Tuned on Two-Nation Theory Debates},
  howpublished = {\url{https://huggingface.co/jamyasir/historical-gpt2-finetuned}},
  year         = {2025}
}

🙌 Author

Muhammad Yasir AI Engineer | Full Stack Developer 📍 Lodhran, Pakistan 🌐 Portfolio ✉️ jamyasir0534@gmail.com 🤗 Hugging Face Profile

devxyasir/historical-gpt2-finetuned

🧠 historical-gpt2-finetuned