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---
language:
- en
license: mit
datasets:
- Open-Orca/SlimOrca
- beaugogh/openorca-multiplechoice-10k
metrics:
- accuracy
model-index:
- name: llama2_7b_merge_orcafamily
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: 56.91
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
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: 81.17
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
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: 51.49
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
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: 49.68
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
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: 75.93
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
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: 23.12
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
name: Open LLM Leaderboard
---
This model is based on the LLama 7b model as a backbone, and datasets from various Orcas have been fine-tuned and merged.
The three models were combined, and the model with the best ARC and MMLU performance was given the highest weight.
First: fine-tuning beaugogh/openorca-multiplechoice-10k on llama2 7b, but using the NEFTune method.
Second: model fine-tuned with the SlimOrca dataset on llama2 7b.
Third : Model with beaugogh/openorca-multiplechoice-10k fine-tuned on llama2 7b.
We'll add the results once we have the official results
# [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_yeen214__llama2_7b_merge_orcafamily)
| Metric |Value|
|---------------------------------|----:|
|Avg. |56.38|
|AI2 Reasoning Challenge (25-Shot)|56.91|
|HellaSwag (10-Shot) |81.17|
|MMLU (5-Shot) |51.49|
|TruthfulQA (0-shot) |49.68|
|Winogrande (5-shot) |75.93|
|GSM8k (5-shot) |23.12|
|