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whisper-tiny-sinhala-20k
Ransaka/whisper-tiny-sinhala-20k
whisper-tiny-sinhala-20k is a automatic speech recognition model from Ransaka. 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
- Nov 27, 2023
- Updated
- Nov 29, 2023
- SHA
- c9232302
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-sinhala-20k
This model is a fine-tuned version of openai/whisper-tiny on the sinhala_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2433
- Wer: 92.9960
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: 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4207 | 0.4 | 1000 | 0.3978 | 221.9058 |
| 0.2966 | 0.8 | 2000 | 0.3009 | 136.3423 |
| 0.226 | 1.2 | 3000 | 0.2661 | 97.6638 |
| 0.2224 | 1.6 | 4000 | 0.2510 | 92.3279 |
| 0.2034 | 2.0 | 5000 | 0.2433 | 92.9960 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Nov 27, 2023
- Updated
- Nov 29, 2023