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whisper-finetuned-cv9-norm
TheRains/whisper-finetuned-cv9-norm
whisper-finetuned-cv9-norm is a automatic speech recognition model from TheRains. 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
- Aug 3, 2023
- Updated
- Aug 4, 2023
- SHA
- 89eaeb92
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 ID - norm
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.4712
- Wer: 282.7881
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: 8
- eval_batch_size: 4
- 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: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 17.6812 | 1.94 | 1000 | 12.3783 | 1360.8144 |
| 6.976 | 3.87 | 2000 | 8.7546 | 241.4815 |
| 2.0938 | 5.81 | 3000 | 7.1760 | 899.5997 |
| 0.3231 | 7.74 | 4000 | 5.4712 | 282.7881 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- id
- Created
- Aug 3, 2023
- Updated
- Aug 4, 2023