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whisper-medium-medical
jilangdi/whisper-medium-medical
whisper-medium-medical is a automatic speech recognition model from jilangdi. 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 6, 2024
- Updated
- Oct 6, 2024
- SHA
- be2e16fb
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 Medium Medical
This model is a fine-tuned version of openai/whisper-medium on the Medical ASR dataset. It achieves the following results on the evaluation set:
- Loss: 0.0995
- Wer: 12.4065
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7532 | 0.1357 | 100 | 0.2695 | 13.0099 |
| 0.2155 | 0.2714 | 200 | 0.2053 | 9.8238 |
| 0.2392 | 0.4071 | 300 | 0.1567 | 8.9549 |
| 0.151 | 0.5427 | 400 | 0.1159 | 6.9273 |
| 0.1439 | 0.6784 | 500 | 0.0995 | 12.4065 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Oct 6, 2024
- Updated
- Oct 6, 2024