Adding Evaluation Results (#1)

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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\|