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whisper-tiny-quran-lite-v1.1
ubulut/whisper-tiny-quran-lite-v1.1
whisper-tiny-quran-lite-v1.1 is a automatic speech recognition model from ubulut. 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
- Jul 6, 2024
- Updated
- Jul 6, 2024
- SHA
- 67ed8840
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 Tiny AR - Quran
This model is a fine-tuned version of openai/whisper-tiny on the quran-whisper-dataset-lite dataset. It achieves the following results on the evaluation set:
- Loss: 2.6327
- Wer: 85.4452
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0003 | 17.2414 | 1000 | 2.5428 | 86.8579 |
| 0.0001 | 34.4828 | 2000 | 2.5570 | 85.6164 |
| 0.0 | 51.7241 | 3000 | 2.6121 | 85.8305 |
| 0.0 | 68.9655 | 4000 | 2.6327 | 85.4452 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- ar
- Created
- Jul 6, 2024
- Updated
- Jul 6, 2024