--- language: - uk license: apache-2.0 base_model: openai/whisper-medium tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: Whisper Medium uk results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: uk split: test args: uk metrics: - name: Wer type: wer value: 10.912533864101288 --- # Whisper Medium uk This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.2943 - Wer: 10.9125 ## 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: 32 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.2039 | 0.9099 | 1000 | 0.2393 | 14.0916 | | 0.0942 | 1.8198 | 2000 | 0.2207 | 11.8428 | | 0.0463 | 2.7298 | 3000 | 0.2303 | 11.5953 | | 0.0156 | 3.6397 | 4000 | 0.2701 | 11.0438 | | 0.0041 | 4.5496 | 5000 | 0.2943 | 10.9125 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1