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language:
- en
- ko
pipeline_tag: text-generation
inference: false
tags:
- pytorch
- Yi-Ko
- 01-ai
- Yi
library_name: transformers
license: apache-2.0
Update @ 2024.01.29 Released Yi-Ko(KoEN)-DUS-9B model 🎉
beomi/Yi-Ko-DUS-9B
Yi-Ko-DUS model serves as DUS-applied and advanced iterations of beomi/Yi-Ko-6B model, benefiting from an expanded vocabulary and the inclusion of Korean/English corpus in its further pretraining.
Yi-Ko-DUS model operates with 9B billion parameters.
This repository focuses on the 9B pretrained version, which is tailored to fit the Hugging Face Transformers format, trained after DUS method applied.
Model Details
Model Developers Junbum Lee (Beomi), Taekyoon Choi (Taekyoon)
Variations Yi-Ko-DUS has 9B model only.
Input Models input text only.
Output Models generate text only.
Model Architecture
Yi-Ko-DUS series models are an auto-regressive language model that uses an optimized transformer architecture based on Llama-2*.
*Yi model architecture is based on Llama2, so it can be loaded via LlamaForCausalLM class on HF.
| Model Name | Training Data | Params | Context Length | GQA | Trained Tokens | LR | Batch Size(per step) |
|---|---|---|---|---|---|---|---|
| Yi-Ko-DUS-9B | A mix of Korean + English online data | 9B | 4k | O | >120B | 5e-5 | 2M tokens |
Vocab Expansion
| Model Name | Vocabulary Size | Description |
|---|---|---|
| Original Yi-Series | 64000 | Sentencepiece BPE |
| Expanded Yi-Ko(DUS) Series | 78464 | Sentencepiece BPE. Added Korean vocab and merges |
Tokenizing "안녕하세요, 오늘은 날씨가 좋네요.ㅎㅎ"
| Model | # of tokens | Tokens |
|---|---|---|
| Original Yi-Series | 47 | ['<0xEC>', '<0x95>', '<0x88>', '<0xEB>', '<0x85>', '<0x95>', '하', '<0xEC>', '<0x84>', '<0xB8>', '<0xEC>', '<0x9A>', '<0x94>', ',', '▁', '<0xEC>', '<0x98>', '<0xA4>', '<0xEB>', '<0x8A>', '<0x98>', '은', '▁', '<0xEB>', '<0x82>', '<0xA0>', '<0xEC>', '<0x94>', '<0xA8>', '가', '▁', '<0xEC>', '<0xA2>', '<0x8B>', '<0xEB>', '<0x84>', '<0xA4>', '<0xEC>', '<0x9A>', '<0x94>', '.', '<0xE3>', '<0x85>', '<0x8E>', '<0xE3>', '<0x85>', '<0x8E>'] |
| Expanded Yi-Ko(DUS) Series | 10 | ['▁안녕', '하세요', ',', '▁오늘은', '▁날', '씨가', '▁좋네요', '.', 'ㅎ', 'ㅎ'] |
| *Equal Korean vocab with Llama-2-Ko Series |
Tokenizing "Llama 2: Open Foundation and Fine-Tuned Chat Models"
| Model | # of tokens | Tokens |
|---|---|---|
| Original Yi-Series | 21 | ['The', '▁Y', 'i', '▁series', '▁models', '▁are', '▁large', '▁language', '▁models', '▁trained', '▁from', '▁scratch', '▁by', '▁developers', '▁at', '▁', '0', '1', '.', 'AI', '.'] |
| Expanded Yi-Ko(DUS) Series | 21 | ['▁The', '▁Y', 'i', '▁series', '▁models', '▁are', '▁large', '▁language', '▁models', '▁trained', '▁from', '▁scratch', '▁by', '▁developers', '▁at', '▁', '0', '1', '.', 'AI', '.'] |
| *Equal Korean vocab with Llama-2-Ko Series | *Since Expanded Yi-Ko Series prepends _ at the beginning of the text(to ensure same tokenization for Korean sentences), it shows negilible difference for the first token on English tokenization. |
Model Benchmark
5-shot Korean Dataset Evaluation
KMMLU: 43.3514 (exact_match, kmmlu_direct)
- +2.58%p than beomi/Yi-Ko-6B
KorQuAD: 80.8798 (exact_match)
- +3.06%p than beomi/Yi-Ko-6B
NSMC: 88.352 (acc)
- +0.3%p than beomi/Yi-Ko-6B
KOBEST COPA: 84.4831 (macro_f1)
- +3.6%p than beomi/Yi-Ko-6B
KOBEST HellaSwag: 52.6099 (macro_f1)
- +2.7%p than beomi/Yi-Ko-6B
Apeach: Korean HateSpeech: 63.4723 (macro_f1)
- +13.6%p than beomi/Yi-Ko-6B
LICENSE
Apache 2.0 (for research)
For commercial purpose, mailto: [email protected] to acquire Yi-Ko sereis commercial license.
Citation
Please use this bibtex below:
@misc {lee_junbum_2024,
author = { {Lee Junbum, Choi Taekyoon} },
title = { Yi-Ko-DUS-9B },
year = 2024,
url = { https://huggingface.co/beomi/Yi-Ko-DUS-9B },
doi = { 10.57967/hf/1707 },
publisher = { Hugging Face }
}
Acknowledgement
The training is supported by TPU Research Cloud program.