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whisper-large-v3-yixing-dialect
lubobill1990/whisper-large-v3-yixing-dialect
whisper-large-v3-yixing-dialect is a machine learning model from lubobill1990. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. 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
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 12, 2025
- Updated
- May 12, 2025
- SHA
- 897d22d8
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. -->
lubobill1990/whisper-large-v3-yixing-dialect
This model is a fine-tuned version of openai/whisper-large-v3 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.0375
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: 8
- eval_batch_size: 8
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_8BIT 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: 5
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6523 | 0.0346 | 50 | 1.8361 |
| 1.1887 | 0.0692 | 100 | 1.4349 |
| 1.1177 | 0.1037 | 150 | 1.3058 |
| 1.2017 | 0.1383 | 200 | 1.2580 |
| 1.2097 | 0.1729 | 250 | 1.2214 |
| 0.8582 | 0.2075 | 300 | 1.1897 |
| 0.8613 | 0.2420 | 350 | 1.1691 |
| 0.9025 | 0.2766 | 400 | 1.1537 |
| 1.0347 | 0.3112 | 450 | 1.1366 |
| 0.8058 | 0.3458 | 500 | 1.1220 |
| 0.8358 | 0.3804 | 550 | 1.1087 |
| 0.9403 | 0.4149 | 600 | 1.1042 |
| 1.0258 | 0.4495 | 650 | 1.0950 |
| 0.976 | 0.4841 | 700 | 1.0891 |
| 0.632 | 0.5187 | 750 | 1.0800 |
| 0.7036 | 0.5533 | 800 | 1.0700 |
| 0.7675 | 0.5878 | 850 | 1.0653 |
| 1.0105 | 0.6224 | 900 | 1.0629 |
| 0.6001 | 0.6570 | 950 | 1.0558 |
| 0.7627 | 0.6916 | 1000 | 1.0524 |
| 0.7371 | 0.7261 | 1050 | 1.0507 |
| 0.6548 | 0.7607 | 1100 | 1.0513 |
| 0.8578 | 0.7953 | 1150 | 1.0455 |
| 0.6846 | 0.8299 | 1200 | 1.0432 |
| 0.785 | 0.8645 | 1250 | 1.0401 |
| 0.819 | 0.8990 | 1300 | 1.0388 |
| 0.9689 | 0.9336 | 1350 | 1.0380 |
| 0.8372 | 0.9682 | 1400 | 1.0375 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.1
- Tokenizers 0.21.1
- Library
- peft
- License
- apache-2.0
- Created
- May 12, 2025
- Updated
- May 12, 2025