metadata
license: llama2
datasets:
- pkupie/mc2_corpus
- togethercomputer/RedPajama-Data-1T
language:
- en
- bo
base_model:
- meta-llama/Llama-2-7b-hf
A continually pre-trained model based on Llama-2-7b-hf.
We use the Tibetan texts in MC^2 and English texts in RedPajama with a proportion of 4:1 for training.
Hyper-parameters:
- lr: 3e-5
- batch size: 1M (2K*512)
- lr scheduler: cosine
- min lr: 1e-6
- lr decay iters: 10240
Citation
If you find this model is useful in your work, please cite it with:
@inproceedings{tao-etal-2024-unlocking,
title = "Unlocking the Potential of Model Merging for Low-Resource Languages",
author = "Tao, Mingxu and
Zhang, Chen and
Huang, Quzhe and
Ma, Tianyao and
Huang, Songfang and
Zhao, Dongyan and
Feng, Yansong",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.508",
doi = "10.18653/v1/2024.findings-emnlp.508",
pages = "8705--8720"
}