whisper-small-ukr-dialects

whisper-small - Fine-tuned for Ukrainian ASR

This model is a fine-tuned version of openai/whisper-small on the ukr dialects audio dataset for Ukrainian speech recognition.

Model Description

Fine-tune openai/whisper-small on ukr-dialects-audio-dataset

Training Details

Training Data

Training Hyperparameters

Training Results

The model was trained for 5000 steps with evaluation every 500 steps. The best checkpoint was selected based on the lowest CER.

Best Model Checkpoint: Step 4500

Final Evaluation Metrics

Validation Set

Test Set

Usage

Using Pipeline (Recommended)

from transformers import pipeline
import torch

device = "cuda:0" if torch.cuda.is_available() else "cpu"

pipe = pipeline(
    "automatic-speech-recognition",
    model="KSE-RESEARCH-Group/whisper-small-ukr-dialects",
    device=device,
)

result = pipe(
    "path/to/audio.wav",
    generate_kwargs={
        "task": "transcribe",
        "language": "ukrainian",
    },
    chunk_length_s=30,
)
print(result["text"])

Using Transformers Directly

from transformers import WhisperForConditionalGeneration, WhisperProcessor
import torch

model_id = "KSE-RESEARCH-Group/whisper-small-ukr-dialects"

processor = WhisperProcessor.from_pretrained(model_id)
model = WhisperForConditionalGeneration.from_pretrained(model_id)

# Move to GPU if available
device = "cuda:0" if torch.cuda.is_available() else "cpu"
model = model.to(device)

# Process audio (audio_array should be a numpy array at 16kHz)
input_features = processor(
    audio_array, 
    sampling_rate=16000, 
    return_tensors="pt"
).input_features.to(device)

# Generate transcription
predicted_ids = model.generate(input_features)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
print(transcription)

Infrastructure

Hardware

Environment

Training Time

Experiment Details

Citation

If you use this model, please cite:

@misc{KSE-RESEARCH-Group-whisper-small-ukr-dialects,
  author = {KSE-RESEARCH-Group},
  title = {whisper-small - Fine-tuned for Ukrainian ASR},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/KSE-RESEARCH-Group/whisper-small-ukr-dialects}
}

License

This model is released under the Apache 2.0 license.

Acknowledgements

• Base model: openai/whisper-small
• Dataset: ukr dialects audio dataset
• Training infrastructure: NVIDIA GeForce RTX 4090