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nb-whisper-small-karelian-CodeSwitching
Mihaj/nb-whisper-small-karelian-CodeSwitching
nb-whisper-small-karelian-CodeSwitching is a automatic speech recognition model from Mihaj. 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
- Jun 13, 2024
- Updated
- Jun 24, 2024
- SHA
- 9b9994ed
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. -->
nb-whisper-small-karelian-CodeSwitching
This model is a fine-tuned version of NbAiLab/nb-whisper-small-verbatim on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7241
- Wer: 0.3278
- Cer: 0.0999
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | Cer |
|---|---|---|---|---|---|
| 0.1848 | 1.1338 | 500 | 0.6758 | 0.4066 | 0.1227 |
| 0.0796 | 2.2676 | 1000 | 0.6685 | 0.3549 | 0.1015 |
| 0.0492 | 3.4014 | 1500 | 0.7090 | 0.3758 | 0.1088 |
| 0.0426 | 4.5351 | 2000 | 0.7095 | 0.3704 | 0.1083 |
| 0.0311 | 5.6689 | 2500 | 0.7148 | 0.3742 | 0.1138 |
| 0.027 | 6.8027 | 3000 | 0.7173 | 0.3454 | 0.1004 |
| 0.0201 | 7.9365 | 3500 | 0.7261 | 0.3813 | 0.1325 |
| 0.0165 | 9.0703 | 4000 | 0.7158 | 0.3417 | 0.0982 |
| 0.0179 | 10.2041 | 4500 | 0.7261 | 0.3495 | 0.1036 |
| 0.0101 | 11.3379 | 5000 | 0.7275 | 0.3315 | 0.0978 |
| 0.0086 | 12.4717 | 5500 | 0.7437 | 0.3400 | 0.1081 |
| 0.0058 | 13.6054 | 6000 | 0.7524 | 0.3410 | 0.1026 |
| 0.0056 | 14.7392 | 6500 | 0.7256 | 0.3407 | 0.1015 |
| 0.0075 | 15.8730 | 7000 | 0.7202 | 0.3312 | 0.0987 |
| 0.0047 | 17.0068 | 7500 | 0.7266 | 0.3359 | 0.1025 |
| 0.0046 | 18.1406 | 8000 | 0.7271 | 0.3312 | 0.0973 |
| 0.0039 | 19.2744 | 8500 | 0.7334 | 0.3353 | 0.0999 |
| 0.0025 | 20.4082 | 9000 | 0.7280 | 0.3295 | 0.0987 |
| 0.0022 | 21.5420 | 9500 | 0.7290 | 0.3254 | 0.0972 |
| 0.0031 | 22.6757 | 10000 | 0.7241 | 0.3278 | 0.0999 |
Framework versions
- Transformers 4.41.2
- 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
- Created
- Jun 13, 2024
- Updated
- Jun 24, 2024