dec10 / README.md

Adding Evaluation Results (#3)

987b5d1 verified 3 months ago

No virus

5.97 kB

	---
	language:
	- en
	license: cc-by-nc-4.0
	tags:
	- merge
	datasets:
	- Intel/orca_dpo_pairs
	- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
	pipeline_tag: text-generation
	model-index:
	- name: dec10
	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: 69.11
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/dec10
	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: 86.46
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/dec10
	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: 64.98
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/dec10
	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: 60.42
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/dec10
	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: 80.74
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/dec10
	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: 70.58
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/dec10
	name: Open LLM Leaderboard
	---
	Slerp Merge of rwitz/go-bruins-v2 and Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp



	![image/png](https://cdn-uploads.huggingface.co/production/uploads/63a259d0f30c46422789d38d/tmdM1fjNAmzV125zWd3_J.png)

	# Go Bruins V2 - A Fine-tuned Language Model

	## Updates

	## Overview

	Go Bruins-V2 is a language model fine-tuned on the rwitz/go-bruins architecture. It's designed to push the boundaries of NLP applications, offering unparalleled performance in generating human-like text.

	## Model Details

	- Developer: Ryan Witzman
	- Base Model: [rwitz/go-bruins](https://huggingface.co/rwitz/go-bruins)
	- Fine-tuning Method: Direct Preference Optimization (DPO)
	- Training Steps: 642
	- Language: English
	- License: MIT

	## Capabilities

	Go Bruins excels in a variety of NLP tasks, including but not limited to:
	- Text generation
	- Language understanding
	- Sentiment analysis

	## Usage

	Warning: This model may output NSFW or illegal content. Use with caution and at your own risk.

	### For Direct Use:

	```python
	from transformers import pipeline

	model_name = "rwitz/go-bruins-v2"
	inference_pipeline = pipeline('text-generation', model=model_name)

	input_text = "Your input text goes here"
	output = inference_pipeline(input_text)

	print(output)
	```


	### Not Recommended For:

	- Illegal activities
	- Harassment
	- Professional advice or crisis situations

	## Training and Evaluation

	Trained on a dataset from [athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW](https://huggingface.co/datasets/athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW), Go Bruins V2 has shown promising improvements over its predecessor, Go Bruins.

	# Evaluations

	\| Metric \| Average \| Arc Challenge \| Hella Swag \| MMLU \| Truthful Q&A \| Winogrande \| GSM8k \|
	\|---------------\|---------\|---------------\|------------\|------\|--------------\|------------\|-------\|
	\| Score \| ?? \| ??.8 \| ??.05\| ??.75 \| ??.7 \| ??.45 \| ??.67 \|

	Note: The original MMLU evaluation has been corrected to include 5-shot data rather than 1-shot data.
	## Contact

	For any inquiries or feedback, reach out to Ryan Witzman on Discord: `rwitz_`.

	---
	## Citations
	```
	@misc{unacybertron7b,
	title={Cybertron: Uniform Neural Alignment},
	author={Xavier Murias},
	year={2023},
	publisher = {HuggingFace},
	journal = {HuggingFace repository},
	howpublished = {\url{https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16}},
	}
	```

	This model card was created with care by Ryan Witzman.
	rewrite this model card for new version called go-bruins-v2 that is finetuned on dpo on the original go-bruins model on athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
	# [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_rwitz__dec10)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|72.05\|
	\|AI2 Reasoning Challenge (25-Shot)\|69.11\|
	\|HellaSwag (10-Shot) \|86.46\|
	\|MMLU (5-Shot) \|64.98\|
	\|TruthfulQA (0-shot) \|60.42\|
	\|Winogrande (5-shot) \|80.74\|
	\|GSM8k (5-shot) \|70.58\|