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whisper-medium-nb-v3
P1NHE4D/whisper-medium-nb-v3
whisper-medium-nb-v3 is a automatic speech recognition model from P1NHE4D. 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
- May 3, 2023
- Updated
- May 4, 2023
- SHA
- 38878f03
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-nb-v3
This model is a fine-tuned version of openai/whisper-medium on the Stortingskorpuset dataset. It achieves the following results on the evaluation set:
- Loss: 0.1948
- Wer: 10.0245
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 8000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4018 | 0.25 | 2000 | 0.4179 | 25.0751 |
| 0.1617 | 1.1 | 4000 | 0.2911 | 16.5849 |
| 0.0885 | 1.35 | 6000 | 0.2264 | 12.5146 |
| 0.0269 | 2.2 | 8000 | 0.1948 | 10.0245 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- nb
- Created
- May 3, 2023
- Updated
- May 4, 2023