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whisper-small-SIT_18_07_26_0551
horhh/whisper-small-SIT_18_07_26_0551
whisper-small-SIT_18_07_26_0551 is a automatic speech recognition model from horhh. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- whisper
- Access
- Public
- Created
- Jul 18, 2026
- Updated
- Jul 18, 2026
- SHA
- eb886399
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-SIT_18_07_26_0551
This model is a fine-tuned version of Pengwin30/whisper-small-fine-tuned on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0578
- Wer: 3.5785
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: 64
- eval_batch_size: 16
- seed: 42
- 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: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.5763 | 1.0 | 87 | 0.0697 | 3.9099 |
| 0.0529 | 2.0 | 174 | 0.0568 | 4.0424 |
| 0.0202 | 3.0 | 261 | 0.0596 | 3.4460 |
| 0.0073 | 4.0 | 348 | 0.0575 | 3.7773 |
| 0.0037 | 5.0 | 435 | 0.0578 | 3.5785 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 2.19.0
- Tokenizers 0.22.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- mit
- Created
- Jul 18, 2026
- Updated
- Jul 18, 2026