README.md

---
license: apache-2.0
model-index:
- name: flyingllama
  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: 24.74
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/flyingllama
      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: 38.35
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/flyingllama
      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: 26.14
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/flyingllama
      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: 41.6
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/flyingllama
      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: 50.12
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/flyingllama
      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=kevin009/flyingllama
      name: Open LLM Leaderboard
---

# Model Card for `kevin009/flyingllama`

## Model Description

`kevin009/flyingllama` is a language model leveraging the Llama architecture. It is tailored for text generation and various natural language processing tasks. The model features a hidden size of 1024, incorporates 24 hidden layers, and is equipped with 16 attention heads. It utilizes a vocabulary comprising 50304 tokens and is fine-tuned using the SiLU activation function.

### Model Usage

This model is well-suited for tasks such as text generation, language modeling, and other natural language processing applications that require understanding and generating human-like language.

### Limitations

Like any model, `kevin009/flyingllama` may have limitations related to its architecture and training data. Users should assess its performance for specific use cases.

---
# [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_kevin009__flyingllama)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |30.16|
|AI2 Reasoning Challenge (25-Shot)|24.74|
|HellaSwag (10-Shot)              |38.35|
|MMLU (5-Shot)                    |26.14|
|TruthfulQA (0-shot)              |41.60|
|Winogrande (5-shot)              |50.12|
|GSM8k (5-shot)                   | 0.00|