gpt2-finetuned-greek-small

Greek (el) GPT2 model - small

<img src="https://huggingface.co/lighteternal/gpt2-finetuned-greek-small/raw/main/GPT2el.png" width="600"/>

A new version (recommended) trained on 5x more data is available at: https://huggingface.co/lighteternal/gpt2-finetuned-greek

By the Hellenic Army Academy (SSE) and the Technical University of Crete (TUC)

• language: el
• licence: apache-2.0
• dataset: ~5GB of Greek corpora
• model: GPT2 (12-layer, 768-hidden, 12-heads, 117M parameters. OpenAI GPT-2 English model, finetuned for the Greek language)
• pre-processing: tokenization + BPE segmentation

Model description

A text generation (autoregressive) model, using Huggingface transformers and fastai based on the English GPT-2(small).

Finetuned with gradual layer unfreezing. This is a more efficient and sustainable alternative compared to training from scratch, especially for low-resource languages.

Based on the work of Thomas Dehaene (ML6) for the creation of a Dutch GPT2: https://colab.research.google.com/drive/1Y31tjMkB8TqKKFlZ5OJ9fcMp3p8suvs4?usp=sharing

How to use

from transformers import pipeline

model = "lighteternal/gpt2-finetuned-greek-small"

generator = pipeline(
    'text-generation',
    device=0,
    model=f'{model}',
    tokenizer=f'{model}')
    
text = "Μια φορά κι έναν καιρό"

print("\\\\
".join([x.get("generated_text") for x in generator(
    text,
    max_length=len(text.split(" "))+15,
    do_sample=True,
    top_k=50,
    repetition_penalty = 1.2,
    add_special_tokens=False,
    num_return_sequences=5,
    temperature=0.95,
    top_p=0.95)]))
    

Training data

We used a small (~5GB) sample from a consolidated Greek corpus based on CC100, Wikimatrix, Tatoeba, Books, SETIMES and GlobalVoices. A bigger corpus is expected to provide better results (T0D0).

Acknowledgement

The research work was supported by the Hellenic Foundation for Research and Innovation (HFRI) under the HFRI PhD Fellowship grant (Fellowship Number:50, 2nd call)

Based on the work of Thomas Dehaene (ML6): https://blog.ml6.eu/dutch-gpt2-autoregressive-language-modelling-on-a-budget-cff3942dd020