---
language:
- en
tags:
- deval
- evaluation
- llama
library_name: transformers
model-index:
- name: roadz/dv-finetuned-211124
  results: []
pipeline_tag: text-generation
---

# 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