jaLLAbi2-7b / README.md

Adding Evaluation Results (#1)

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	---
	license: apache-2.0
	tags:
	- merge
	- mergekit
	- lazymergekit
	- FelixChao/WestSeverus-7B-DPO-v2
	- bardsai/jaskier-7b-dpo-v5.6
	- AbacusResearch/haLLAwa3
	- cognitivecomputations/WestLake-7B-v2-laser
	model-index:
	- name: jaLLAbi2-7b
	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: 71.67
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/jaLLAbi2-7b
	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: 88.29
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/jaLLAbi2-7b
	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: 64.92
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/jaLLAbi2-7b
	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: 70.16
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/jaLLAbi2-7b
	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: 83.35
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/jaLLAbi2-7b
	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: 71.95
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/jaLLAbi2-7b
	name: Open LLM Leaderboard
	---

	# jaLLAbi2-7b

	jaLLAbi2-7b is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
	* [FelixChao/WestSeverus-7B-DPO-v2](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2)
	* [bardsai/jaskier-7b-dpo-v5.6](https://huggingface.co/bardsai/jaskier-7b-dpo-v5.6)
	* [AbacusResearch/haLLAwa3](https://huggingface.co/AbacusResearch/haLLAwa3)
	* [cognitivecomputations/WestLake-7B-v2-laser](https://huggingface.co/cognitivecomputations/WestLake-7B-v2-laser)

	## 🧩 Configuration

	\```yaml
	models:
	- model: eren23/ogno-monarch-jaskier-merge-7b
	# No parameters necessary for base model
	- model: FelixChao/WestSeverus-7B-DPO-v2
	#Emphasize the beginning of Vicuna format models
	parameters:
	weight: 0.2
	density: 0.59
	- model: bardsai/jaskier-7b-dpo-v5.6
	parameters:
	weight: 0.2
	density: 0.55
	# Vicuna format
	- model: AbacusResearch/haLLAwa3
	parameters:
	weight: 0.3
	density: 0.55
	- model: cognitivecomputations/WestLake-7B-v2-laser
	parameters:
	weight: 0.3
	density: 0.55

	merge_method: dare_ties
	base_model: eren23/ogno-monarch-jaskier-merge-7b
	parameters:
	int8_mask: true
	dtype: bfloat16
	random_seed: 0
	\```
	# [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_AbacusResearch__jaLLAbi2-7b)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|75.06\|
	\|AI2 Reasoning Challenge (25-Shot)\|71.67\|
	\|HellaSwag (10-Shot) \|88.29\|
	\|MMLU (5-Shot) \|64.92\|
	\|TruthfulQA (0-shot) \|70.16\|
	\|Winogrande (5-shot) \|83.35\|
	\|GSM8k (5-shot) \|71.95\|