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whisper-large-ch
Alexlinander/whisper-large-ch
whisper-large-ch is a automatic speech recognition model from Alexlinander. 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 21, 2024
- Updated
- Jun 22, 2024
- SHA
- f9a18df2
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_finetune_Formosa
This model is a fine-tuned version of openai/whisper-large on the Formosa dataset. It achieves the following results on the evaluation set:
- Loss: 0.1572
- Wer: 9.8143
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: 16
- eval_batch_size: 8
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2883 | 0.1018 | 500 | 0.1850 | 13.1693 |
| 0.2687 | 0.2035 | 1000 | 0.1702 | 10.7376 |
| 0.2417 | 0.3053 | 1500 | 0.1626 | 10.1341 |
| 0.2628 | 0.4070 | 2000 | 0.1572 | 9.8143 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.13.1+cu116
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Jun 21, 2024
- Updated
- Jun 22, 2024