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whisper-small-ha-lora-v2
therealbee/whisper-small-ha-lora-v2
whisper-small-ha-lora-v2 is a machine learning model from therealbee. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- Sep 18, 2026
- Updated
- Sep 19, 2026
- SHA
- 1ccff902
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-small-ha-lora-v2
This model is a fine-tuned version of therealbee/whisper-small-ha-finetuned on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1832
- Wer: 15.2170
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: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2686 | 0.5242 | 200 | 0.1977 | 16.7368 |
| 0.2343 | 1.0472 | 400 | 0.1896 | 16.1059 |
| 0.2109 | 1.5714 | 600 | 0.1869 | 15.9816 |
| 0.1981 | 2.0944 | 800 | 0.1831 | 15.1118 |
| 0.1858 | 2.6186 | 1000 | 0.1832 | 15.2170 |
Framework versions
- PEFT 0.19.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
- Library
- peft
- Created
- Sep 18, 2026
- Updated
- Sep 19, 2026