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whisper-small-tel
sagarchapara/whisper-small-tel
whisper-small-tel is a automatic speech recognition model from sagarchapara. 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
- Feb 27, 2025
- Updated
- Mar 12, 2025
- SHA
- 080ebb3a
Base models
Datasets
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 Telugu - Fine-tuned
This model is a fine-tuned version of openai/whisper-large-v2 on the Telugu Audio Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 3.5889
- Wer: 92.3967
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.384 | 0.1797 | 250 | 0.9966 | 96.1662 |
| 0.434 | 0.3595 | 500 | 1.4886 | 98.5007 |
| 0.4014 | 0.5392 | 750 | 1.4760 | 97.7940 |
| 0.3318 | 0.7189 | 1000 | 1.5314 | 97.7511 |
| 0.3014 | 0.8986 | 1250 | 1.5504 | 97.8368 |
| 0.2213 | 1.0784 | 1500 | 1.6095 | 97.3656 |
| 0.2212 | 1.2581 | 1750 | 1.6825 | 96.1662 |
| 0.2323 | 1.4378 | 2000 | 1.5175 | 97.6012 |
| 0.2049 | 1.6175 | 2250 | 2.0035 | 97.7940 |
| 0.1834 | 1.7973 | 2500 | 1.6968 | 96.4232 |
| 0.2012 | 1.9770 | 2750 | 1.7613 | 97.3013 |
| 0.1426 | 2.1567 | 3000 | 1.5106 | 95.9734 |
| 0.1344 | 2.3364 | 3250 | 1.7199 | 95.5665 |
| 0.1512 | 2.5162 | 3500 | 1.9328 | 94.8169 |
| 0.1346 | 2.6959 | 3750 | 1.7806 | 96.0805 |
| 0.1211 | 2.8756 | 4000 | 2.0429 | 95.6736 |
| 0.0824 | 3.0554 | 4250 | 2.0699 | 95.3309 |
| 0.0936 | 3.2351 | 4500 | 2.0379 | 96.1876 |
| 0.0946 | 3.4148 | 4750 | 2.1346 | 95.9092 |
| 0.0904 | 3.5945 | 5000 | 2.1195 | 95.0311 |
| 0.0937 | 3.7743 | 5250 | 1.7738 | 95.1810 |
| 0.0836 | 3.9540 | 5500 | 2.0081 | 95.1167 |
| 0.0525 | 4.1337 | 5750 | 2.3687 | 94.9240 |
| 0.0562 | 4.3134 | 6000 | 2.2252 | 95.1381 |
| 0.0506 | 4.4932 | 6250 | 2.5513 | 95.5022 |
| 0.0592 | 4.6729 | 6500 | 2.5357 | 95.6736 |
| 0.0521 | 4.8526 | 6750 | 2.4758 | 95.8235 |
| 0.0276 | 5.0324 | 7000 | 2.8255 | 94.9454 |
| 0.0278 | 5.2121 | 7250 | 2.6255 | 94.7740 |
| 0.0311 | 5.3918 | 7500 | 3.0046 | 94.4956 |
| 0.0269 | 5.5715 | 7750 | 2.8301 | 94.7312 |
| 0.0242 | 5.7513 | 8000 | 2.8859 | 94.2386 |
| 0.0255 | 5.9310 | 8250 | 2.5873 | 93.4676 |
| 0.0157 | 6.1107 | 8500 | 3.4027 | 93.6175 |
| 0.0092 | 6.2904 | 8750 | 3.5842 | 93.6389 |
| 0.0118 | 6.4702 | 9000 | 3.2694 | 93.9602 |
| 0.0086 | 6.6499 | 9250 | 3.3464 | 93.5318 |
| 0.01 | 6.8296 | 9500 | 3.4414 | 93.4461 |
| 0.0065 | 7.0093 | 9750 | 3.3491 | 92.6108 |
| 0.002 | 7.1891 | 10000 | 3.5889 | 92.3967 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- te
- Created
- Feb 27, 2025
- Updated
- Mar 12, 2025