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whisper-small-zh-TW
xmzhu/whisper-small-zh-TW
whisper-small-zh-TW is a automatic speech recognition model from xmzhu. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Dec 20, 2022
- Updated
- Dec 21, 2022
- SHA
- d75cc79b
Model card
From the Hugging Face model README
<!-- 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 Small Chinese (Taiwanese Mandarin)
This model is a fine-tuned version of xmzhu/whisper-small-zh on the mozilla-foundation/common_voice_11_0 zh-TW dataset. It achieves the following results on the evaluation set:
- Loss: 0.2639
- Wer: 42.9887
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: 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0058 | 6.02 | 1000 | 0.2445 | 43.0911 |
| 0.0006 | 13.02 | 2000 | 0.2639 | 42.9887 |
| 0.0003 | 20.01 | 3000 | 0.2787 | 43.1934 |
| 0.0002 | 27.0 | 4000 | 0.2877 | 43.5415 |
| 0.0002 | 33.02 | 5000 | 0.2910 | 43.5824 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- zh
- Created
- Dec 20, 2022
- Updated
- Dec 21, 2022