Open Source Release

Polish Whisper

Whisper ASR models fine-tuned for Polish Language - winner of Whisper Fine Tuning Event Challenge

Polish Whisper

// About

What it is

At bards.ai, we fine-tuned OpenAI's Whisper model specifically for the Polish language as part of Hugging Face's global Whisper Fine-Tuning Sprint.

Our model took first place in the Polish category, standing out for its exceptional transcription accuracy and robustness across diverse Polish audio sources.

We focused on minimizing word error rate while preserving the natural flow of spoken Polish, ensuring the model performs well across interviews, podcasts, casual speech, and formal recordings. The result is a state-of-the-art Polish ASR model ready for real-world use in transcription, accessibility, and voice-driven applications.

// Performance

Evaluation metrics

  • Loss

    0.3684

  • WER

    7.2802%

// Training

Hyperparameters

Learning rate
1e-05
Train batch size
8
Eval batch size
4
Seed
42
Gradient accumulation steps
8
Total train batch size
64
Optimizer
Adam (betas=(0.9, 0.999), epsilon=1e-08)
LR scheduler type
linear
LR scheduler warmup steps
500
Training steps
2100
Mixed precision training
Native AMP

// Need a model like this?

We build production models. Then we open-source the useful ones.

Book a meeting