--- language: - uk license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_1 metrics: - wer model-index: - name: Whisper Small Ukrainian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.1 type: mozilla-foundation/common_voice_16_1 config: uk split: None args: 'config: uk, split: test' metrics: - name: Wer type: wer value: 26.357029928161317 --- # Whisper Small Ukrainian This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set: - Loss: 0.2744 - Wer: 26.3570 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.278 | 0.47 | 1000 | 0.3330 | 31.8004 | | 0.2662 | 0.94 | 2000 | 0.2961 | 29.4969 | | 0.1403 | 1.42 | 3000 | 0.2796 | 27.3209 | | 0.1105 | 1.89 | 4000 | 0.2702 | 26.2724 | | 0.0719 | 2.36 | 5000 | 0.2744 | 26.3570 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.2.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2