--- library_name: transformers language: - zh license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 metrics: - wer model-index: - name: Whisper Small zh-TW - hanson92828 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.0 type: mozilla-foundation/common_voice_16_0 config: zh-TW split: test args: 'config: zh-TW, split: test' metrics: - name: Wer type: wer value: 203.22126031809944 --- # Whisper Small zh-TW - hanson92828 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.2087 - Wer: 203.2213 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.0974 | 1.3263 | 1000 | 0.1997 | 167.3042 | | 0.0218 | 2.6525 | 2000 | 0.1987 | 228.9309 | | 0.0094 | 3.9788 | 3000 | 0.2022 | 221.2603 | | 0.0025 | 5.3050 | 4000 | 0.2087 | 203.2213 | ### Framework versions - Transformers 4.46.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.19.2 - Tokenizers 0.20.1