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whisper-small-serbian-v2
samil24/whisper-small-serbian-v2
whisper-small-serbian-v2 is a automatic speech recognition model from samil24. 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
- Aug 26, 2025
- Updated
- Aug 27, 2025
- SHA
- aebbc697
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-serbian-v2
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2957
- Wer: 14.0126
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 1250
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.304 | 0.9234 | 500 | 0.2736 | 21.4309 |
| 0.2213 | 1.8458 | 1000 | 0.2192 | 17.9671 |
| 0.1528 | 2.7682 | 1500 | 0.2149 | 18.1085 |
| 0.0876 | 3.6907 | 2000 | 0.2211 | 16.4412 |
| 0.0598 | 4.6131 | 2500 | 0.2254 | 15.9645 |
| 0.0335 | 5.5355 | 3000 | 0.2396 | 15.7533 |
| 0.0172 | 6.4580 | 3500 | 0.2494 | 15.8825 |
| 0.0109 | 7.3804 | 4000 | 0.2568 | 15.4303 |
| 0.0067 | 8.3029 | 4500 | 0.2684 | 15.4198 |
| 0.0038 | 9.2253 | 5000 | 0.2710 | 14.9571 |
| 0.0036 | 10.1477 | 5500 | 0.2738 | 14.9327 |
| 0.0019 | 11.0702 | 6000 | 0.2772 | 14.7406 |
| 0.0019 | 11.9935 | 6500 | 0.2744 | 14.8262 |
| 0.0018 | 12.9160 | 7000 | 0.2770 | 14.5102 |
| 0.0011 | 13.8384 | 7500 | 0.2784 | 14.3688 |
| 0.0005 | 14.7608 | 8000 | 0.2814 | 14.2762 |
| 0.0002 | 15.6833 | 8500 | 0.2870 | 14.1767 |
| 0.0002 | 16.6057 | 9000 | 0.2904 | 14.1523 |
| 0.0001 | 17.5282 | 9500 | 0.2934 | 14.0563 |
| 0.0001 | 18.4506 | 10000 | 0.2944 | 13.9742 |
| 0.0001 | 19.3730 | 10500 | 0.2957 | 14.0126 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Aug 26, 2025
- Updated
- Aug 27, 2025