--- language: - id license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer model-index: - name: Whisper Small Id - Ezra William results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 13.0 type: mozilla-foundation/common_voice_13_0 config: id split: None args: 'config: id, split: test' metrics: - name: Wer type: wer value: 17.216589861751153 --- # Whisper Small Id - Ezra William This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3271 - Wer: 17.2166 ## 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: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.1836 | 1.9194 | 1000 | 0.2526 | 17.7512 | | 0.0409 | 3.8388 | 2000 | 0.2741 | 17.4885 | | 0.0046 | 5.7582 | 3000 | 0.3143 | 17.3548 | | 0.0022 | 7.6775 | 4000 | 0.3271 | 17.2166 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1