metadata

datasets:
  - sciq
  - metaeval/ScienceQA_text_only
  - GAIR/lima
  - Open-Orca/OpenOrca
  - openbookqa
language:
  - en
tags:
  - upstage
  - llama
  - instruct
  - instruction
pipeline_tag: text-generation

LLaMa-30b-instruct model card

Model Details

Developed by: Upstage
Backbone Model: LLaMA
Variations: It has different model parameter sizes and sequence lengths: 30B/1024, 30B/2048, 65B/1024
Language(s): English
Library: HuggingFace Transformers
License: This model is under a Non-commercial Bespoke License and governed by the Meta license. You should only use this repository if you have been granted access to the model by filling out this form, but have either lost your copy of the weights or encountered issues converting them to the Transformers format
Where to send comments: Instructions on how to provide feedback or comments on a model can be found by opening an issue in the Hugging Face community's model repository
Contact: For questions and comments about the model, please email [email protected]

Dataset Details

Used Datasets

No other data was used except for the dataset mentioned above

Prompt Template

### System:
{System}

### User:
{User}

### Assistant:
{Assistant}

Hardware and Software

Hardware: We utilized an A100x8 for training our model
Training Factors: We fine-tuned this model using a combination of the DeepSpeed library and the HuggingFace trainer

Evaluation Results

Overview

We conducted a performance evaluation based on the tasks being evaluated on the Open LLM Leaderboard. We evaluated our model on four benchmark datasets, which include ARC-Challenge, HellaSwag, MMLU, and TruthfulQA. We used the lm-evaluation-harness repository, specifically commit b281b0921b636bc36ad05c0b0b0763bd6dd43463.

Main Results

Model	Average	ARC	HellaSwag	MMLU	TruthfulQA
llama-65b-instruct (Ours, Local Reproduction)	69.4	67.6	86.5	64.9	58.8
llama-30b-instruct-2048 (Ours, Open LLM Leaderboard)	67.0	64.9	84.9	61.9	56.3
Llama-2-70b-chat-hf	66.8	64.6	85.9	63.9	52.8
llama-30b-instruct (Ours, Open LLM Leaderboard)	65.2	62.5	86.2	59.4	52.8
falcon-40b-instruct	63.4	61.6	84.3	55.4	52.5
llama-65b	62.1	57.6	84.3	63.4	43.0

Scripts

Prepare evaluation environments:

# clone the repository
git clone https://github.com/EleutherAI/lm-evaluation-harness.git

# check out the specific commit
git checkout b281b0921b636bc36ad05c0b0b0763bd6dd43463

# change to the repository directory
cd lm-evaluation-harness

Ethical Issues

Ethical Considerations

There were no ethical issues involved, as we did not include the benchmark test set or the training set in the model's training process.

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