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whisper-base-ta
navin-kumar-j/whisper-base-ta
whisper-base-ta is a automatic speech recognition model from navin-kumar-j. 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 2, 2025
- Updated
- Apr 29, 2025
- SHA
- de8efded
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 Base Ta - Navin Kumar J
This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2913
- Wer: 1.5234
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 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2192 | 0.2773 | 1000 | 0.3592 | 1.1204 |
| 0.2076 | 0.5546 | 2000 | 0.3164 | 1.1192 |
| 0.1881 | 0.8319 | 3000 | 0.2993 | 1.5272 |
| 0.1504 | 1.1093 | 4000 | 0.2913 | 1.5234 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- ta
- Created
- Apr 2, 2025
- Updated
- Apr 29, 2025