GPT-2 Fine-Tuned Mental Health Chatbot

📝 Model Description

This is a fine-tuned GPT-2 model specialized for mental health support conversations. It provides empathetic responses to users feeling distressed, stressed, or anxious. This model is trained on a custom dataset with carefully crafted conversational data.

🚀 Use case: AI-driven mental health support chatbot.
🛠 Base Model: GPT-2
📁 Dataset: Custom dataset based on intents.json + Kaggle conversational dataset

📂 Model Files

File	Description
`config.json`	Model configuration
`pytorch_model.bin`	Model weights
`tokenizer.json`	Tokenizer configuration
`vocab.json`	Vocabulary file
`training_args.bin`	Training hyperparameters
`generation_config.json`	Generation settings

🏗️ Training Details

The model was fine-tuned on Google Colab using the Hugging Face Transformers library.
Training was performed using:

Optimizer: AdamW
Learning Rate: 5e-5
Batch Size: 8
Epochs: 5

📊 Training Performance

Epoch	Training Loss	Validation Loss
1	1.1932	1.0248
2	0.7532	0.7870
3	0.7520	0.6927
4	0.6018	0.6580
5	0.5192	0.6403

🚀 How to Use the Model

You can load and use the model with Hugging Face Transformers:

from transformers import pipeline

# Load the model
chatbot = pipeline("text-generation", model="TheCarBun/GPT-2-fine-tuned-mental-health")

# Test the chatbot
user_input = "I feel so alone."
response = chatbot(f"User: {user_input} AI:", max_length=50)
print(response[0]['generated_text'])

📝 Note: If running locally, install dependencies first:

pip install transformers torch

🛠️ Future Improvements

Expand dataset to cover more diverse mental health conversations
Improve response coherence by fine-tuning with reinforcement learning
Optimize model size for deployment on mobile devices

📜 License

This model is licensed under the Apache 2.0 License. You are free to use, modify, and distribute it with proper attribution.

📌 Hugging Face Model Link: GPT-2 Fine-Tuned Mental Health

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