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---
language:
- en
license: apache-2.0
library_name: transformers
datasets:
- monology/VMware-open-instruct-higgsfield
pipeline_tag: text-generation
model-index:
- name: openinstruct-mistral-7b
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: 59.73
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b
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: 82.77
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b
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: 60.55
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b
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: 48.76
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b
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: 79.56
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b
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: 50.49
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b
name: Open LLM Leaderboard
---
# OpenInstruct Mistral-7B
**1st among commercially-usable 7B models on the Open LLM Leaderboard!\***
This is [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) finetuned on [VMware/open-instruct](https://huggingface.co/datasets/VMware/open-instruct).
Quantized to FP16 and released under the [Apache-2.0](https://choosealicense.com/licenses/apache-2.0) license by myself.
Compute generously provided by [Higgsfield AI](https://higgsfield.ai/model/655559e6b5777dab620095e0).
## Prompt format: Alpaca
```
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
[your instruction goes here]
### Response:
```
## Recommended preset:
- temperature: 0.2
- top_k: 50
- top_p 0.95
- repetition_penalty: 1.1
\*as of 21 Nov 2023. "commercially-usable" includes both an open-source base model and a *non-synthetic* open-source finetune dataset. updated leaderboard results available [here](https://huggingfaceh4-open-llm-leaderboard.hf.space).
# [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_monology__openinstruct-mistral-7b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |63.64|
|AI2 Reasoning Challenge (25-Shot)|59.73|
|HellaSwag (10-Shot) |82.77|
|MMLU (5-Shot) |60.55|
|TruthfulQA (0-shot) |48.76|
|Winogrande (5-shot) |79.56|
|GSM8k (5-shot) |50.49|
|