hassanaliemon

/

bn_rag_llama3-8b

like 4

I just completed a thorough performance analysis of this model and wanted to share findings that could help the community:

🔍 Key Findings

✅ Excellent Performance (4.9/5):

• Creative writing and story continuation
• Text completion in Bengali
• Mixed Bengali-English content generation
• Simple math operations

❌ Poor Performance (0-25% accuracy):

• Factual question answering
• Structured instruction following (Alpaca format)
• Information retrieval tasks
• RAG applications (despite the name)

📊 Testing Methodology

• 7 different task categories tested
• Multiple prompt formats (simple, structured, Alpaca-style)
• Performance benchmarking on dual Tesla T4 GPUs
• Real-world use case evaluation

💡 Bottom Line

This model is excellent for creative applications but not suitable for factual Q&A or information retrieval. The "RAG" in the name is misleading - it's better described as a creative writing assistant.

🎯 Use Cases

✅ RECOMMENDED FOR:

• Creative writing assistance
• Content brainstorming
• Story/blog generation
• Text completion
• Language learning exercises

❌ NOT RECOMMENDED FOR:

• Factual question answering
• Educational Q&A systems
• Information retrieval
• Production chatbots

📊 Full Analysis

Complete no[tebook with benchmarks and methodology:
https://www.kaggle.com/code/risadmalik/bengali-llama-reality-check-hassanaliemon-bn-r-8b

Hope this helps others evaluate if this model fits their use case! Happy to answer any questions about the testing methodology.