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whisper-large-v2-zh-TW
WANGTINGTING/whisper-large-v2-zh-TW
whisper-large-v2-zh-TW is a automatic speech recognition model from WANGTINGTING. 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
- Jun 25, 2024
- Updated
- Jun 25, 2024
- SHA
- bc6049a8
Base models
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 large Chinese language vo1
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1847
- Cer: 5.4054
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.4346 | 0.16 | 2 | 0.2856 | 8.1081 |
| 0.5535 | 0.32 | 4 | 0.1927 | 5.4054 |
| 0.3467 | 0.48 | 6 | 0.1847 | 5.4054 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- zh
- Created
- Jun 25, 2024
- Updated
- Jun 25, 2024