--- license: apache-2.0 base_model: arun100/whisper-base-uk-1 tags: - whisper-event - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper Base Ukrainian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs uk_ua type: google/fleurs config: uk_ua split: test args: uk_ua metrics: - name: Wer type: wer value: 33.562978427279056 --- # Whisper Base Ukrainian This model is a fine-tuned version of [arun100/whisper-base-uk-1](https://huggingface.co/arun100/whisper-base-uk-1) on the google/fleurs uk_ua dataset. It achieves the following results on the evaluation set: - Loss: 0.4710 - Wer: 33.5630 ## 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: 2.5e-07 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2683 | 95.0 | 1000 | 0.4710 | 33.5630 | | 0.142 | 190.0 | 2000 | 0.4714 | 33.8344 | | 0.0871 | 285.0 | 3000 | 0.4782 | 33.9596 | | 0.0656 | 380.0 | 4000 | 0.4830 | 33.7230 | | 0.0595 | 476.0 | 5000 | 0.4847 | 33.7161 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.16.2.dev0 - Tokenizers 0.15.0