| --- |
| language: |
| - zh |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - generated_from_trainer |
| datasets: |
| - formospeech/tat_asr_aligned |
| model-index: |
| - name: Whisper Tiny Taiwanese Simulated Android |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # Whisper Tiny Taiwanese Simulated Android |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the TAT ASR Aligned dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7438 |
| - Cer: 11.6466 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 64 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1362 |
| - training_steps: 13620 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Cer | |
| |:-------------:|:-------:|:-----:|:---------------:|:-------:| |
| | 0.3611 | 0.9985 | 681 | 0.4700 | 20.9285 | |
| | 0.2547 | 1.9971 | 1362 | 0.4463 | 15.1381 | |
| | 0.1658 | 2.9956 | 2043 | 0.4418 | 13.8355 | |
| | 0.1045 | 3.9941 | 2724 | 0.4723 | 13.4539 | |
| | 0.0687 | 4.9927 | 3405 | 0.4987 | 13.4172 | |
| | 0.0456 | 5.9912 | 4086 | 0.5397 | 13.2578 | |
| | 0.0326 | 6.9897 | 4767 | 0.5761 | 12.9786 | |
| | 0.0219 | 7.9883 | 5448 | 0.6007 | 13.0098 | |
| | 0.0167 | 8.9868 | 6129 | 0.6061 | 12.7120 | |
| | 0.0122 | 9.9853 | 6810 | 0.6446 | 12.8573 | |
| | 0.0087 | 10.9839 | 7491 | 0.6544 | 12.7846 | |
| | 0.0053 | 11.9824 | 8172 | 0.6783 | 12.3071 | |
| | 0.0041 | 12.9809 | 8853 | 0.6960 | 12.3634 | |
| | 0.002 | 13.9795 | 9534 | 0.7046 | 12.2334 | |
| | 0.0012 | 14.9780 | 10215 | 0.7138 | 12.0635 | |
| | 0.0004 | 15.9765 | 10896 | 0.7239 | 12.0304 | |
| | 0.0002 | 16.9751 | 11577 | 0.7270 | 11.7646 | |
| | 0.0001 | 17.9736 | 12258 | 0.7367 | 11.6746 | |
| | 0.0001 | 18.9721 | 12939 | 0.7418 | 11.6619 | |
| | 0.0001 | 19.9707 | 13620 | 0.7438 | 11.6466 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.3 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
