CapybaraHermes-2.5-Mistral-7B / README.md

Adding Evaluation Results (#2)

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	---
	language:
	- en
	license: apache-2.0
	library_name: trl
	tags:
	- distilabel
	- dpo
	- rlaif
	- rlhf
	datasets:
	- argilla/dpo-mix-7k
	base_model: teknium/OpenHermes-2.5-Mistral-7B
	model-index:
	- name: CapybaraHermes-2.5-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: 65.78
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/CapybaraHermes-2.5-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: 85.45
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/CapybaraHermes-2.5-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: 63.13
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/CapybaraHermes-2.5-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: 56.91
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/CapybaraHermes-2.5-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=argilla/CapybaraHermes-2.5-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: 59.29
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/CapybaraHermes-2.5-Mistral-7B
	name: Open LLM Leaderboard
	---

	# CapybaraHermes-2.5-Mistral-7B
	<div>
	<img src="https://cdn-uploads.huggingface.co/production/uploads/60420dccc15e823a685f2b03/Vmr0FtTvnny6Snm-UDM_n.png">
	</div>

	<p align="center">
	<a href="https://github.com/argilla-io/distilabel">
	<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
	</a>
	</p>


	This model is the launching partner of the [capybara-dpo dataset](https://huggingface.co/datasets/argilla/distilabel-capybara-dpo-9k-binarized) build with ⚗️ distilabel. It's a preference tuned [OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B).

	CapybaraHermes has been preference tuned with LoRA and TRL for 3 epochs using argilla's [dpo mix 7k](https://huggingface.co/datasets/argilla/dpo-mix-7k).

	To test the impact on multi-turn performance we have used MTBench. We also include the Nous Benchmark results and Mistral-7B-Instruct-v0.2 for reference as it's a strong 7B model on MTBench:

	\| Model \| AGIEval \| GPT4All \| TruthfulQA \| Bigbench \| MTBench First Turn \| MTBench Second Turn \| Nous avg. \| MTBench avg. \|
	\|-----------------------------------\|---------\|---------\|------------\|----------\|------------\|-------------\|-----------\|--------------\|
	\| argilla/CapybaraHermes-2.5-Mistral-7B \| 43.8 \| 73.35 \| 57.07 \| 42.44 \| 8.24375 \| 7.5625 \| 54.16 \| 7.903125 \|
	\| teknium/OpenHermes-2.5-Mistral-7B \| 42.75 \| 72.99 \| 52.99 \| 40.94 \| 8.25 \| 7.2875 \| 52.42 \| 7.76875 \|
	\| Mistral-7B-Instruct-v0.2 \| 38.5 \| 71.64 \| 66.82 \| 42.29 \| 7.8375 \| 7.1 \| 54.81 \| 7.46875 \|

	The most interesting aspect in the context of the capybara-dpo dataset is the increased performance in MTBench Second Turn scores.

	For the merge lovers, we also preference tuned Beagle14-7B with a mix of capybara-dpo and distilabel orca pairs using the same recipe as NeuralBeagle (see [ YALL - Yet Another LLM Leaderboard](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard) for reference):

	\| Model \|AGIEval\|GPT4All\|TruthfulQA\|Bigbench\|Average\|
	\|------------------------------------------------------------------------------------------------------------------------------------\|------:\|------:\|---------:\|-------:\|------:\|
	\|[DistilabelBeagle14-7B](https://huggingface.co/dvilasuero/DistilabelBeagle14-7B)\| 45.29\| 76.92\| 71.66\| 48.78\| 60.66\|




	## Model Details

	### Model Description

	<!-- Provide a longer summary of what this model is. -->

	This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

	- Developed by: Argilla
	- Shared by [optional]: Argilla
	- Model type: 7B chat model
	- Language(s) (NLP): English
	- License: Same as OpenHermes
	- Finetuned from model [optional]: [OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)


	# [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_argilla__CapybaraHermes-2.5-Mistral-7B)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|68.14\|
	\|AI2 Reasoning Challenge (25-Shot)\|65.78\|
	\|HellaSwag (10-Shot) \|85.45\|
	\|MMLU (5-Shot) \|63.13\|
	\|TruthfulQA (0-shot) \|56.91\|
	\|Winogrande (5-shot) \|78.30\|
	\|GSM8k (5-shot) \|59.29\|