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whisper-tiny_to_chinese_accent_further_analysis_r
rogramss/whisper-tiny_to_chinese_accent_further_analysis_r
whisper-tiny_to_chinese_accent_further_analysis_r is a automatic speech recognition model from rogramss. 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
- Mar 18, 2025
- Updated
- Mar 18, 2025
- SHA
- 2ce3bba8
Base models
Datasets
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 tiny Chinese
This model is a fine-tuned version of openai/whisper-tiny on the Chinese English 'R' Phonemes dataset. It achieves the following results on the evaluation set:
- Loss: 0.3367
- Wer: 14.0050
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: 2
- eval_batch_size: 1
- 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: 500
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1284 | 1.5038 | 1000 | 0.3222 | 14.5818 |
| 0.0295 | 3.0075 | 2000 | 0.3241 | 13.9149 |
| 0.0027 | 4.5113 | 3000 | 0.3367 | 14.0050 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- en
- Created
- Mar 18, 2025
- Updated
- Mar 18, 2025