language:
- en
tags:
- llama
license: other
metrics:
- MMLU
- ARC
- HellaSwag
- TruthfulQA
🥳 Platypus-30B has arrived!
Platypus-30B is an instruction fine-tuned model based on the LLaMA-30B transformer architecture and takes advantage of LoRA.
Metric | Value |
---|---|
MMLU (5-shot) | 65.4 |
ARC (25-shot) | 64.6 |
HellaSwag (10-shot) | 84.3 |
TruthfulQA (0-shot) | 45.8 |
Avg. | 65 |
Model Details
- Trained by: Cole Hunter & Ariel Lee
- Model type: Platypus-30B is an auto-regressive language model based on the LLaMA transformer architecture.
- Language(s): English
- License for base weights: License for the base LLaMA model's weights is Meta's non-commercial bespoke license.
Hyperparameter | Value |
---|---|
33B | |
6656 | |
60 | |
52 |
Training Dataset
Dataset of highly filtered and curated question and answer pairs. Release TBD.
Training Procedure
lilloukas/Platypus-30B
was instruction fine-tuned using LoRA on 4 A100 80GB. For training details and inference instructions please see the Platypus-30B GitHub repo.
Limitations and bias
The base LLaMA model is trained on various data, some of which may contain offensive, harmful, and biased content that can lead to toxic behavior. See Section 5.1 of the LLaMA paper. We have not performed any studies to determine how fine-tuning on the aforementioned datasets affect the model's behavior and toxicity. Do not treat chat responses from this model as a substitute for human judgment or as a source of truth. Please use responsibly.
Citations
@article{touvron2023llama,
title={LLaMA: Open and Efficient Foundation Language Models},
author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and Rodriguez, Aurelien and Joulin, Armand and Grave, Edouard and Lample, Guillaume},
journal={arXiv preprint arXiv:2302.13971},
year={2023}
}
@article{DBLP:journals/corr/abs-2106-09685,
author = {Edward J. Hu and
Yelong Shen and
Phillip Wallis and
Zeyuan Allen{-}Zhu and
Yuanzhi Li and
Shean Wang and
Weizhu Chen},
title = {LoRA: Low-Rank Adaptation of Large Language Models},
journal = {CoRR},
year = {2021},
url = {https://arxiv.org/abs/2106.09685},
}