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whisper-train
anvitamanne/whisper-train
whisper-train is a automatic speech recognition model from anvitamanne. 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
- Jan 7, 2026
- Updated
- Jan 7, 2026
- SHA
- 33b7b05b
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-train
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2384
- Wer: 0.2870
- Cer: 0.0749
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: Use OptimizerNames.RMSPROP and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 19760
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.1235 | 1.0006 | 1000 | 0.1177 | 0.3478 | 0.0882 |
| 0.0642 | 2.0011 | 2000 | 0.1340 | 0.3398 | 0.0888 |
| 0.0337 | 3.0017 | 3000 | 0.1533 | 0.3365 | 0.0845 |
| 0.0196 | 4.0022 | 4000 | 0.1664 | 0.3262 | 0.0841 |
| 0.0126 | 5.0028 | 5000 | 0.1725 | 0.3167 | 0.0812 |
| 0.0085 | 6.0033 | 6000 | 0.1950 | 0.3327 | 0.0841 |
| 0.0063 | 7.0039 | 7000 | 0.1855 | 0.3034 | 0.0807 |
| 0.0045 | 8.0045 | 8000 | 0.1932 | 0.3060 | 0.0797 |
| 0.0033 | 9.0050 | 9000 | 0.1954 | 0.3015 | 0.0788 |
| 0.0024 | 10.0056 | 10000 | 0.2011 | 0.3070 | 0.0800 |
| 0.0019 | 11.0061 | 11000 | 0.1976 | 0.2917 | 0.0776 |
| 0.0015 | 12.0067 | 12000 | 0.2122 | 0.3028 | 0.0792 |
| 0.0011 | 13.0072 | 13000 | 0.2010 | 0.2969 | 0.0779 |
| 0.0006 | 14.0078 | 14000 | 0.2187 | 0.2975 | 0.0784 |
| 0.0005 | 15.0084 | 15000 | 0.2249 | 0.2956 | 0.0767 |
| 0.0003 | 16.0089 | 16000 | 0.2263 | 0.2916 | 0.0761 |
| 0.0002 | 17.0095 | 17000 | 0.2314 | 0.2891 | 0.0763 |
| 0.0001 | 18.0100 | 18000 | 0.2346 | 0.2886 | 0.0756 |
| 0.0 | 19.0106 | 19000 | 0.2384 | 0.2870 | 0.0749 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.2
- Tokenizers 0.22.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Jan 7, 2026
- Updated
- Jan 7, 2026