Adding Evaluation Results (#1)

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	---
	language:
	- en
	license: apache-2.0
	pipeline_tag: text-generation
	model-index:
	- name: Kant-Test-0.1-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: 62.37
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zardos/Kant-Test-0.1-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: 82.84
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zardos/Kant-Test-0.1-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: 63.38
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zardos/Kant-Test-0.1-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: 49.62
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zardos/Kant-Test-0.1-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: 78.3
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zardos/Kant-Test-0.1-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: 37.98
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zardos/Kant-Test-0.1-Mistral-7B
	name: Open LLM Leaderboard
	---

	# Model Yaml

	The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters.
	Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.

	For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/).

	## Model Architecture

	Mistral-7B-v0.1 is a transformer model, with the following architecture choices:
	- Grouped-Query Attention
	- Sliding-Window Attention
	- Byte-fallback BPE tokenizer

	## Troubleshooting

	- If you see the following error:
	```
	KeyError: 'mistral'
	```
	- Or:
	```
	NotImplementedError: Cannot copy out of meta tensor; no data!
	```

	Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.

	## Notice

	Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms.

	## The Mistral AI Team

	Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.

	# [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_Zardos__Kant-Test-0.1-Mistral-7B)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|62.42\|
	\|AI2 Reasoning Challenge (25-Shot)\|62.37\|
	\|HellaSwag (10-Shot) \|82.84\|
	\|MMLU (5-Shot) \|63.38\|
	\|TruthfulQA (0-shot) \|49.62\|
	\|Winogrande (5-shot) \|78.30\|
	\|GSM8k (5-shot) \|37.98\|