This repository contains a GPT2-small model trained on Japanese Wikipedia dataset.
We splitted the dataset into three subsets - train, valid and test sets. Both tokenizer and model were trained on the train set. Train set contains around 540M tokens.
The model architecture is the same as GPT-2 small model (n_ctx: 1024, n_embd 768, n_head: 12, n_layer: 12) except for a vocabulary size.
The vocabulary size is set to 32,000 instead of an original size of 50,257.
transformers.GPT2LMHeadModel is used for training.
SentencePiece is used as a tokenizer for this model.
We utilized 1,000,000 sentences from train set.
The vocabulary size was 32,000.
add_dummy_prefix option was set to
True because Japanese words are not separated by whitespaces.
After training, the tokenizer model was imported as
because it supports SentencePiece models and it does not add any special tokens as default,
which is useful expecially for a text generation task.
The model was trained on the train set for 30 epochs with batch size 32. Each sample contained 1024 tokens.
We utilized Adam optimizer. Learning rate was linearly increased from
1e-4 during the first 10,000 steps.
A clip norm was set to
Test set perplexity of the trained model was 29.13.
Please refer to GitHub for more training details.
First, install dependecies.
$ pip install transformers==4.10.0 torch==1.8.1 sentencepiece==0.1.96
Then use pipeline to generate sentences.
>>> import transformers >>> pipeline = transformers.pipeline("text-generation", "colorfulscoop/gpt2-small-ja") >>> pipeline("統計的機械学習でのニューラルネットワーク", do_sample=True, top_p=0.95, top_k=50, num_return_sequences=3)
Note: The default model configuration
config.json sets parameters for text generation with
Please set these parameters when you need to use different parameters.
We recommend to specify
revision to load the model for reproducibility.
|Revision||Date of Wikipedia dump|
|20210820.1.0||Aug 20, 2021|
|20210301.1.0||March 1, 2021|
You can specify
revision as follows.
# Example of pipeline transformers.pipeline("text-generation", "colorfulscoop/gpt2-small-ja", revision="20210820.1.0") # Example of AutoModel transformers.AutoModel.from_pretrained("colorfulscoop/gpt2-small-ja", revision="20210820.1.0")
All the models included in this repository are licensed under Creative Commons Attribution-ShareAlike 3.0.
Disclaimer: The model potentially has possibility that it generates similar texts in the training data, texts not to be true, or biased texts. Use of the model is at your sole risk. Colorful Scoop makes no warranty or guarantee of any outputs from the model. Colorful Scoop is not liable for any trouble, loss, or damage arising from the model output.
Author: Colorful Scoop
- Downloads last month