Vardis/Whisper-Large-v2-Greek
4
Fine-Tuned Whisper Large
This is a Large-sized Whisper model fine-tuned for Greek speech transcription. It has 1.5B parameters and achieves improved transcription performance over the medium model.
- WER: 12.06%
- CER: 6.20%
Training Results
Model Details
- Model Type: Whisper (Large)
- Fine-tuned From: OpenAI Whisper Large
- Language(s): Greek
- Parameters: 1.5B
How to Use
from transformers import WhisperProcessor, WhisperForConditionalGeneration
from peft import PeftModel
import torch
device = "cuda" if torch.cuda.is_available() else "cpu"
# Load base model and Greek fine-tuned LoRA weights
base_model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v2").to(device)
model = PeftModel.from_pretrained(base_model, "Vardis/Whisper-Large-v2-Greek").to(device)
processor = WhisperProcessor.from_pretrained("Vardis/Whisper-Large-v2-Greek")
# Load your audio waveform (e.g., using librosa or torchaudio)
audio_input = ...
# Generate transcription
inputs = processor(audio_input, return_tensors="pt").input_features.to(device)
predicted_ids = model.generate(inputs)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
print(transcription)Context / Reference
This model was developed as part of the work described in:
Georgilas, V., Stafylakis, T. (2025). _Automatic Speech Recognition for Greek Medical Dictation_. The paper focuses on Greek medical ASR research in general and is not primarily about the model itself, but provides context for its development. Users are welcome to use the model freely for research and practical applications.
BibTeX citation:
@misc{georgilas2025greekasr,
title={Automatic Speech Recognition for Greek Medical Dictation},
author={Vardis Georgilas and Themos Stafylakis},
year={2025},
note={Available at: https://www.arxiv.org/abs/2509.23550}
}