metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny AR - BH
results: []
Whisper tiny AR - BH
This model is a fine-tuned version of openai/whisper-tiny on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:
- Loss: 0.0099
- Wer: 0.1017
- Cer: 0.0375
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0107 | 1.0 | 313 | 0.0098 | 0.1102 | 0.0433 |
| 0.0081 | 2.0 | 626 | 0.0087 | 0.1043 | 0.0376 |
| 0.0086 | 3.0 | 939 | 0.0092 | 0.0995 | 0.0346 |
| 0.0045 | 4.0 | 1252 | 0.0099 | 0.0994 | 0.0335 |
| 0.0023 | 5.0 | 1565 | 0.0108 | 0.1023 | 0.0394 |
| 0.001 | 6.0 | 1878 | 0.0117 | 0.1021 | 0.0353 |
| 0.0004 | 7.0 | 2191 | 0.0124 | 0.1012 | 0.0344 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0