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whisper-medium-nepali
kiranpantha/whisper-medium-nepali
whisper-medium-nepali is a automatic speech recognition model from kiranpantha. 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
- Dec 18, 2024
- Updated
- Dec 23, 2024
- SHA
- 31d8a8b2
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 Medium Nepali - Kiran Pantha
This model is a fine-tuned version of openai/whisper-medium on the OpenSLR54 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1608
- Wer: 21.9907
- Cer: 5.3068
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 0.2877 | 0.3597 | 300 | 13.1055 | 0.2588 | 48.6574 |
| 0.1865 | 0.7194 | 600 | 10.0741 | 0.2052 | 39.9537 |
| 0.1155 | 1.0791 | 900 | 8.1217 | 0.1633 | 31.8981 |
| 0.0992 | 1.4388 | 1200 | 7.6923 | 0.1577 | 30.6250 |
| 0.094 | 1.7986 | 1500 | 7.1969 | 0.1418 | 28.3796 |
| 0.0454 | 2.1583 | 1800 | 6.7308 | 0.1472 | 26.6898 |
| 0.0333 | 2.5180 | 2100 | 6.6353 | 0.1512 | 27.0602 |
| 0.0446 | 2.8777 | 2400 | 6.25 | 0.1409 | 25.5556 |
| 0.0204 | 3.2374 | 2700 | 6.5399 | 0.1513 | 25.8796 |
| 0.016 | 3.5971 | 3000 | 5.9674 | 0.1560 | 24.8380 |
| 0.0166 | 3.9568 | 3300 | 6.0592 | 0.1573 | 25.0926 |
| 0.0052 | 4.3165 | 3600 | 5.7802 | 0.1566 | 23.3796 |
| 0.0068 | 4.6763 | 3900 | 5.5233 | 0.1544 | 22.7083 |
| 0.0013 | 5.0360 | 4200 | 5.4756 | 0.1568 | 22.7546 |
| 0.001 | 5.3957 | 4500 | 0.1606 | 22.0139 | 5.3178 |
| 0.0017 | 5.7554 | 4800 | 0.1608 | 21.9907 | 5.3068 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.20.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- ne
- Created
- Dec 18, 2024
- Updated
- Dec 23, 2024