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whisper_base_en
Eyesiga/whisper_base_en
whisper_base_en is a automatic speech recognition model from Eyesiga. 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
- Feb 29, 2024
- Updated
- Feb 29, 2024
- SHA
- 55b7ff18
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 base english
This model is a fine-tuned version of openai/whisper-base.en on the Sunbird dataset. It achieves the following results on the evaluation set:
- Loss: 0.2710
- Wer: 7.7095
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.395 | 3.33 | 1000 | 0.1988 | 7.4860 |
| 0.0295 | 6.67 | 2000 | 0.2389 | 7.3743 |
| 0.0026 | 10.0 | 3000 | 0.2645 | 7.5978 |
| 0.0011 | 13.33 | 4000 | 0.2710 | 7.7095 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- en
- Created
- Feb 29, 2024
- Updated
- Feb 29, 2024