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
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
Detailed results can be found here
| 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 |