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whisper-tiny-2000
Noursene/whisper-tiny-2000
whisper-tiny-2000 is a automatic speech recognition model from Noursene. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- whisper
- Access
- Public
- Created
- May 20, 2024
- Updated
- May 20, 2024
- SHA
- 185bfe2f
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 Small Eng - noursene
This model is a fine-tuned version of openai/whisper-small-2000 on the medical audio trascription dataset. It achieves the following results on the evaluation set:
- Loss: 0.1612
- Wer: 10.5366
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.191 | 3.0257 | 500 | 0.2308 | 14.0727 |
| 0.0375 | 6.0514 | 1000 | 0.1570 | 10.9975 |
| 0.0045 | 9.0772 | 1500 | 0.1594 | 10.7598 |
| 0.0029 | 12.1029 | 2000 | 0.1612 | 10.5366 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Languages
- eng
- Created
- May 20, 2024
- Updated
- May 20, 2024