README.md

---
license: cc-by-nc-nd-4.0
model-index:
- name: caigun-lora-model-33B
  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: 22.7
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=APMIC/caigun-lora-model-33B
      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: 25.04
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=APMIC/caigun-lora-model-33B
      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: 23.12
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=APMIC/caigun-lora-model-33B
      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: 0.0
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=APMIC/caigun-lora-model-33B
      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: 49.57
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=APMIC/caigun-lora-model-33B
      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=APMIC/caigun-lora-model-33B
      name: Open LLM Leaderboard
---

This is model finetuned on fake news detection.

Model Details:

Model Name: caigun-lora-model-33B

Model Version: 1.0

Date Created: 2023/11/17

Model Overview:

Intended Use:  
caigun-lora-model-33B is a LLM designed for various purpose.

Training Data:  
fake news related dataset

Model Architecture:  
It is based on LLaMA architecture.

Training Procedure:    
[Stay tuned for updates]

Model Performance:  
[Stay tuned for updates]


Potential Risks:  
It's important to consider ethical implications related to the use of our model.


Updates and Version History:  
Version 1.0: finetuned on fake news detection.
# [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_APMIC__caigun-lora-model-33B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |20.07|
|AI2 Reasoning Challenge (25-Shot)|22.70|
|HellaSwag (10-Shot)              |25.04|
|MMLU (5-Shot)                    |23.12|
|TruthfulQA (0-shot)              | 0.00|
|Winogrande (5-shot)              |49.57|
|GSM8k (5-shot)                   | 0.00|