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whisper-small-telugu_learning-rate-1e-5-batch-size-32
kaarthu2003/whisper-small-telugu_learning-rate-1e-5-batch-size-32
whisper-small-telugu_learning-rate-1e-5-batch-size-32 is a automatic speech recognition model from kaarthu2003. 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
- Apr 12, 2025
- Updated
- Apr 24, 2025
- SHA
- dbecc8fa
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-telugu_learning-rate-1e-5-batch-size-32
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: 0.2913
- Wer: 0.3679
- Cer: 0.0992
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: 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: 400
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.5388 | 1.0900 | 400 | 0.1649 | 0.5455 | 0.1796 |
| 0.1218 | 2.1801 | 800 | 0.1323 | 0.5317 | 0.1889 |
| 0.0883 | 3.2701 | 1200 | 0.1302 | 0.3957 | 0.1174 |
| 0.0675 | 4.3602 | 1600 | 0.1365 | 0.4234 | 0.1324 |
| 0.0505 | 5.4502 | 2000 | 0.1449 | 0.3825 | 0.1042 |
| 0.0389 | 6.5402 | 2400 | 0.1614 | 0.3788 | 0.1032 |
| 0.0267 | 7.6303 | 2800 | 0.1790 | 0.3732 | 0.1007 |
| 0.0182 | 8.7203 | 3200 | 0.1951 | 0.3682 | 0.0990 |
| 0.0111 | 9.8104 | 3600 | 0.2162 | 0.3672 | 0.0976 |
| 0.0068 | 10.9004 | 4000 | 0.2250 | 0.3659 | 0.0973 |
| 0.004 | 11.9905 | 4400 | 0.2386 | 0.3731 | 0.1005 |
| 0.0021 | 13.0791 | 4800 | 0.2513 | 0.3663 | 0.0980 |
| 0.0011 | 14.1692 | 5200 | 0.2658 | 0.3646 | 0.0966 |
| 0.0006 | 15.2592 | 5600 | 0.2718 | 0.3682 | 0.0973 |
| 0.0004 | 16.3492 | 6000 | 0.2851 | 0.3693 | 0.0986 |
| 0.0003 | 17.4393 | 6400 | 0.2854 | 0.3667 | 0.0983 |
| 0.0002 | 18.5293 | 6800 | 0.2886 | 0.3670 | 0.0991 |
| 0.0001 | 19.6194 | 7200 | 0.2913 | 0.3679 | 0.0992 |
Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Apr 12, 2025
- Updated
- Apr 24, 2025