--- language: - nan license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_1 - mozilla-foundation/common_voice_15_0 model-index: - name: Whisper Small Taiwanese results: [] --- # Whisper Small Taiwanese This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 and the Common Voice 15.0 datasets. It achieves the following results on the evaluation set: - Loss: 0.3736 - Cer: 29.5906 ## 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: 100 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2295 | 1.13 | 3500 | 0.4268 | 32.4577 | | 0.179 | 1.29 | 4000 | 0.4088 | 32.1109 | | 0.161 | 1.45 | 4500 | 0.3923 | 30.9241 | | 0.1607 | 1.61 | 5000 | 0.3840 | 30.1640 | | 0.1336 | 1.77 | 5500 | 0.3783 | 29.7573 | | 0.1258 | 1.93 | 6000 | 0.3736 | 29.5906 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2 - Datasets 2.18.0 - Tokenizers 0.15.2