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whisper-small-denoising
Taeyeun72/whisper-small-denoising
whisper-small-denoising is a automatic speech recognition model from Taeyeun72. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- whisper
- Access
- Public
- Created
- Oct 19, 2023
- Updated
- Oct 19, 2023
- SHA
- 6fcdb42a
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-kor3_de
This model is a fine-tuned version of openai/whisper-small-denoising on the whisper-kor3_de dataset. It achieves the following results on the evaluation set:
- Loss: 0.5477
- Wer: 31.5495
- Cer: 15.9235
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.366 | 0.21 | 50 | 1.0427 | 36.9851 | 17.8672 |
| 0.7035 | 0.42 | 100 | 0.7269 | 34.3514 | 17.0516 |
| 0.526 | 0.64 | 150 | 0.5843 | 35.7803 | 17.8672 |
| 0.5013 | 0.85 | 200 | 0.5556 | 33.1185 | 15.3365 |
| 0.403 | 1.06 | 250 | 0.5383 | 32.6142 | 15.2756 |
| 0.3058 | 1.27 | 300 | 0.5339 | 37.7136 | 18.9267 |
| 0.3081 | 1.48 | 350 | 0.5323 | 34.7716 | 17.3718 |
| 0.3131 | 1.69 | 400 | 0.5260 | 31.6615 | 15.8396 |
| 0.2857 | 1.91 | 450 | 0.5245 | 32.1098 | 14.8487 |
| 0.1625 | 2.12 | 500 | 0.5284 | 31.6895 | 14.8258 |
| 0.1899 | 2.33 | 550 | 0.5284 | 31.8577 | 15.8244 |
| 0.1646 | 2.54 | 600 | 0.5329 | 32.2499 | 16.4875 |
| 0.183 | 2.75 | 650 | 0.5315 | 31.5775 | 15.0393 |
| 0.179 | 2.97 | 700 | 0.5291 | 31.4374 | 14.7572 |
| 0.1048 | 3.18 | 750 | 0.5402 | 31.5775 | 14.8106 |
| 0.1057 | 3.39 | 800 | 0.5418 | 31.8296 | 15.7863 |
| 0.0965 | 3.6 | 850 | 0.5429 | 31.7456 | 15.9921 |
| 0.1098 | 3.81 | 900 | 0.5451 | 32.6422 | 16.8534 |
| 0.0902 | 4.03 | 950 | 0.5453 | 31.5495 | 15.9006 |
| 0.0795 | 4.24 | 1000 | 0.5477 | 31.5495 | 15.9235 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Languages
- ko
- Created
- Oct 19, 2023
- Updated
- Oct 19, 2023