metadata
library_name: transformers
license: llama2
datasets:
- aqua_rat
- microsoft/orca-math-word-problems-200k
- m-a-p/CodeFeedback-Filtered-Instruction
Llama-3-Smaug-8B
Built with Meta Llama 3
This model was built using a new Smaug recipe for improving performance on real world multi-turn conversations applied to meta-llama/Meta-Llama-3-70B-Instruct.
The model outperforms Llama-3-70B-Instruct substantially, and is on par with GPT-4-Turbo, on MT-Bench (see below).
Model Description
- Developed by: Abacus.AI
- License: https://llama.meta.com/llama3/license/
- Finetuned from model: meta-llama/Meta-Llama-3-70B-Instruct.
Evaluation
MT-Bench
########## First turn ##########
score
model turn
Smaug-Llama-3-70B-Instruct 1 9.40000
GPT-4-Turbo 1 9.37500
Meta-Llama-3-70B-Instruct 1 9.21250
########## Second turn ##########
score
model turn
Smaug-Llama-3-70B-Instruct 2 9.0125
GPT-4-Turbo 2 9.0000
Meta-Llama-3-70B-Instruct 2 8.8000
########## Average ##########
score
model
Smaug-Llama-3-70B-Instruct 9.206250
GPT-4-Turbo 9.187500
Meta-Llama-3-70B-Instruct 9.006250
Model | First turn | Second Turn | Average |
---|---|---|---|
Smaug-Llama-3-70B-Instruct | 9.40 | 9.01 | 9.21 |
GPT-4-Turbo | 9.38 | 9.00 | 9.19 |
Meta-Llama-3-70B-Instruct | 9.21 | 8.80 | 9.01 |
This version of Smaug uses new techniques and new data compared to Smaug-72B, and more information will be released later on. For now, see the previous Smaug paper: https://arxiv.org/abs/2402.13228.