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whisper-small-ko-new
mvbnh/whisper-small-ko-new
whisper-small-ko-new is a automatic speech recognition model from mvbnh. 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
- Jul 16, 2024
- Updated
- Jul 19, 2024
- SHA
- ff731d24
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 Ko
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0919
- Wer: 5.0143
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 0.0956 | 0.0718 | 100 | 0.1442 | 11.5193 |
| 0.0808 | 0.1437 | 200 | 0.1401 | 10.9622 |
| 0.0621 | 0.2155 | 300 | 0.1385 | 10.7815 |
| 0.052 | 0.2874 | 400 | 0.1372 | 10.4803 |
| 0.0442 | 0.3592 | 500 | 0.1401 | 9.7124 |
| 0.0454 | 0.4310 | 600 | 0.1369 | 10.7213 |
| 0.0483 | 0.5029 | 700 | 0.1365 | 10.8568 |
| 0.0493 | 0.5747 | 800 | 0.1329 | 9.1251 |
| 0.0393 | 0.6466 | 900 | 0.1253 | 8.5379 |
| 0.0619 | 0.7184 | 1000 | 0.1227 | 7.7699 |
| 0.0863 | 0.7902 | 1100 | 0.1193 | 8.4325 |
| 0.0786 | 0.8621 | 1200 | 0.1165 | 8.4927 |
| 0.0825 | 0.9339 | 1300 | 0.1130 | 8.5379 |
| 0.0707 | 1.0057 | 1400 | 0.1085 | 7.3483 |
| 0.0254 | 1.0776 | 1500 | 0.1049 | 6.3996 |
| 0.0216 | 1.1494 | 1600 | 0.1043 | 6.2189 |
| 0.0204 | 1.2213 | 1700 | 0.1025 | 6.9568 |
| 0.0222 | 1.2931 | 1800 | 0.1025 | 6.2491 |
| 0.0231 | 1.3649 | 1900 | 0.1032 | 6.7761 |
| 0.0258 | 1.4368 | 2000 | 0.1004 | 7.1224 |
| 0.0228 | 1.5086 | 2100 | 0.1000 | 7.2429 |
| 0.0222 | 1.5805 | 2200 | 0.0995 | 5.8576 |
| 0.0197 | 1.6523 | 2300 | 0.0959 | 5.4811 |
| 0.0239 | 1.7241 | 2400 | 0.0952 | 6.9568 |
| 0.0223 | 1.7960 | 2500 | 0.0948 | 6.6255 |
| 0.0145 | 1.8678 | 2600 | 0.0931 | 5.7823 |
| 0.022 | 1.9397 | 2700 | 0.0906 | 5.4058 |
| 0.011 | 2.0115 | 2800 | 0.0916 | 5.5112 |
| 0.007 | 2.0833 | 2900 | 0.0921 | 5.2552 |
| 0.0065 | 2.1552 | 3000 | 0.0924 | 6.0533 |
| 0.0088 | 2.2270 | 3100 | 0.0928 | 5.3757 |
| 0.0063 | 2.2989 | 3200 | 0.0931 | 5.2552 |
| 0.0058 | 2.3707 | 3300 | 0.0922 | 5.2853 |
| 0.0086 | 2.4425 | 3400 | 0.0924 | 5.1950 |
| 0.0149 | 2.5144 | 3500 | 0.0918 | 5.3305 |
| 0.0087 | 2.5862 | 3600 | 0.0915 | 5.3456 |
| 0.0081 | 2.6580 | 3700 | 0.0918 | 5.2251 |
| 0.0083 | 2.7299 | 3800 | 0.0922 | 5.3305 |
| 0.0062 | 2.8017 | 3900 | 0.0920 | 5.0896 |
| 0.0077 | 2.8736 | 4000 | 0.0919 | 5.0143 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- hi
- Created
- Jul 16, 2024
- Updated
- Jul 19, 2024