| --- |
| library_name: transformers |
| language: |
| - nan |
| license: apache-2.0 |
| base_model: openai/whisper-medium |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_16_1 |
| metrics: |
| - wer |
| model-index: |
| - name: Hokkien-to-Tai Lo Whisper ver 3 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 16.0 |
| type: mozilla-foundation/common_voice_16_1 |
| config: nan-tw |
| split: test |
| args: 'config: hi, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 82.85779502396713 |
| --- |
| |
| <!-- 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 3 |
|
|
| This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5026 |
| - Wer: 82.8578 |
|
|
| ## 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 | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 5.9959 | 0.2581 | 800 | 1.1302 | 99.9772 | |
| | 0.8265 | 0.5161 | 1600 | 0.7367 | 92.8555 | |
| | 0.6895 | 0.7742 | 2400 | 0.6409 | 87.4001 | |
| | 0.5814 | 1.0323 | 3200 | 0.5745 | 85.9849 | |
| | 0.4864 | 1.2903 | 4000 | 0.5512 | 85.4143 | |
| | 0.4662 | 1.5484 | 4800 | 0.5334 | 85.8480 | |
| | 0.4421 | 1.8065 | 5600 | 0.5154 | 83.6339 | |
| | 0.449 | 2.0645 | 6400 | 0.5097 | 83.3600 | |
| | 0.3807 | 2.3226 | 7200 | 0.5058 | 83.0861 | |
| | 0.3783 | 2.5806 | 8000 | 0.5026 | 82.8578 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.49.0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
| |
