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whisper-small-denoising_2
Taeyeun72/whisper-small-denoising_2
whisper-small-denoising_2 is a automatic speech recognition model from Taeyeun72. 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
- Oct 20, 2023
- Updated
- Oct 21, 2023
- SHA
- 2f82f7e3
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_2
This model is a fine-tuned version of openai/whisper-small on the whisper-kor3_de_2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3685
- Wer: 23.2718
- Cer: 10.5941
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: 200
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.3178 | 0.21 | 50 | 0.3333 | 23.0343 | 11.1119 |
| 0.2684 | 0.42 | 100 | 0.3293 | 22.9024 | 10.6660 |
| 0.279 | 0.64 | 150 | 0.3264 | 23.1662 | 10.8458 |
| 0.2813 | 0.85 | 200 | 0.3314 | 28.3905 | 14.9597 |
| 0.2363 | 1.06 | 250 | 0.3325 | 31.3720 | 16.7002 |
| 0.1909 | 1.27 | 300 | 0.3333 | 26.4908 | 13.0538 |
| 0.171 | 1.48 | 350 | 0.3384 | 24.4063 | 12.1044 |
| 0.1699 | 1.69 | 400 | 0.3330 | 22.6649 | 10.3711 |
| 0.1824 | 1.91 | 450 | 0.3336 | 23.3509 | 10.8242 |
| 0.0784 | 2.12 | 500 | 0.3425 | 22.7441 | 10.4574 |
| 0.0694 | 2.33 | 550 | 0.3492 | 23.2982 | 10.7379 |
| 0.0946 | 2.54 | 600 | 0.3442 | 24.2744 | 11.4212 |
| 0.0785 | 2.75 | 650 | 0.3486 | 22.6913 | 10.4646 |
| 0.0838 | 2.97 | 700 | 0.3466 | 22.7441 | 10.5941 |
| 0.0423 | 3.18 | 750 | 0.3600 | 24.2480 | 11.3780 |
| 0.0448 | 3.39 | 800 | 0.3615 | 23.0871 | 10.5509 |
| 0.0492 | 3.6 | 850 | 0.3640 | 23.3509 | 10.6228 |
| 0.04 | 3.81 | 900 | 0.3649 | 23.4565 | 10.5941 |
| 0.0385 | 4.03 | 950 | 0.3635 | 24.1689 | 11.2558 |
| 0.0276 | 4.24 | 1000 | 0.3685 | 23.2718 | 10.5941 |
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
- License
- apache-2.0
- Languages
- ko
- Created
- Oct 20, 2023
- Updated
- Oct 21, 2023