---
language:
- en
license: llama2
tags:
- information retrieval
- reranker
inference: false
model-index:
- name: rank_vicuna_7b_v1_fp16
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 44.62
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=castorini/rank_vicuna_7b_v1_fp16
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 65.67
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=castorini/rank_vicuna_7b_v1_fp16
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 44.14
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=castorini/rank_vicuna_7b_v1_fp16
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 45.13
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=castorini/rank_vicuna_7b_v1_fp16
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 66.61
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=castorini/rank_vicuna_7b_v1_fp16
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 0.0
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=castorini/rank_vicuna_7b_v1_fp16
      name: Open LLM Leaderboard
---

# RankVicuna (FP16) Model Card

## Model Details

RankVicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT.

- **Developed by:** [Castorini](https://github.com/castorini)
- **Model type:** An auto-regressive language model based on the transformer architecture
- **License:** Llama 2 Community License Agreement	
- **Finetuned from base model:** [Llama 2](https://arxiv.org/abs/2307.09288)

This specific model is a 7B variant and is trained with data augmentation.
It is also worth noting that it is converted to FP16.

### Model Sources

- **Repository:** https://github.com/castorini/rank_llm
- **Paper:** https://arxiv.org/abs/2309.15088

## Uses

The primary use of RankVicuna is research at the intersection of large language models and retrieval.
The primary intended users of the model are researchers and hobbyists in natural language processing and information retrieval.

## Training Details

RankVicuna is finetuned from `lmsys/vicuna-7b-v1.5` with supervised instruction fine-tuning.

## Evaluation

RankVicuna is currently evaluated on DL19/DL20. See more details in our [paper](https://arxiv.org/pdf/2309.15088.pdf).
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_castorini__rank_vicuna_7b_v1_fp16)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |44.36|
|AI2 Reasoning Challenge (25-Shot)|44.62|
|HellaSwag (10-Shot)              |65.67|
|MMLU (5-Shot)                    |44.14|
|TruthfulQA (0-shot)              |45.13|
|Winogrande (5-shot)              |66.61|
|GSM8k (5-shot)                   | 0.00|