GPT-2 model for Text Generation in luxembourgish language, trained on 667 MB of text data, consisting of RTL.lu news articles, comments, parlament speeches, the luxembourgish Wikipedia, Newscrawl, Webcrawl and subtitles. The training took place on a 32 GB Nvidia Tesla V100

with an initial learning rate of 5e-5
with Batch size 4
for 109 hours
for 30 epochs
using the transformers library

more detailed training information can be found in the "trainer_state.json".

Usage

python

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("laurabernardy/LuxGPT2")

model = AutoModelForCausalLM.from_pretrained("laurabernardy/LuxGPT2")

Limitations and Biases

See the GPT2 model card for considerations on limitations and bias. See the GPT2 documentation for details on GPT2.