--- library_name: transformers language: - nan license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_12_0 metrics: - wer model-index: - name: Hokkien-to-Tai Lo Whisper ver 1.1 results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: Common Voice 16.0 type: mozilla-foundation/common_voice_12_0 config: nan-tw split: test args: 'config: hi, split: test' metrics: - type: wer value: 133.72270187912648 name: Wer --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Hokkien-to-Tai Lo Whisper ver 1.1 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: 0.7563 - Wer: 133.7227 ## 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-06 - train_batch_size: 8 - eval_batch_size: 16 - seed: 42 - optimizer: Use OptimizerNames.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: 1000 - training_steps: 8000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:--------:| | 5.7198 | 0.5135 | 800 | 1.4813 | 136.8207 | | 1.1293 | 1.0270 | 1600 | 1.0268 | 128.2885 | | 0.9323 | 1.5404 | 2400 | 0.8802 | 131.1833 | | 0.7797 | 2.0539 | 3200 | 0.8011 | 132.2499 | | 0.6692 | 2.5674 | 4000 | 0.7563 | 133.7227 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.5.1+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0