Model Card for roadz/dv-finetuned-211124

This model is fine-tuned for evaluating LLM outputs in RAG scenarios, focusing on:

• Hallucination detection
• Attribution accuracy
• Summary completeness
• Response relevancy

Model Details

Model Architecture

• Base Model: LLaMA-3.1-8B
• Architecture Type: llama
• Parameters: Not specified
• Training Type: Fine-tuned for evaluation

Hardware Requirements

• Minimum GPU Memory: 16GB
• Recommended GPU Memory: 24GB
• Format: SafeTensors

Usage

This model is designed for the De-Val subnet and requires specific pipeline code for evaluation tasks.

Generation Configuration

• Max Length: Not specified
• Temperature: 0.6
• Top-p: 0.9
• Top-k: 50

Training

The model was fine-tuned on evaluation tasks including:

• Hallucination detection scenarios
• Attribution verification tasks
• Summary completeness assessment
• Response relevancy evaluation

Limitations

• Designed specifically for evaluation tasks
• Requires De-Val pipeline code
• Not intended for general text generation

Last Updated

2024-11-21