metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper base AR - BH
results: []
Whisper base AR - BH
This model is a fine-tuned version of openai/whisper-base on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:
- Loss: 0.0124
- Wer: 11.8561
- Cer: 3.6023
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 0.0124 | 0.2895 | 800 | 6.9720 | 0.0166 | 21.3510 |
| 0.0076 | 0.5790 | 1600 | 4.4857 | 0.0124 | 14.3371 |
| 0.0042 | 0.8685 | 2400 | 4.2342 | 0.0112 | 13.1816 |
| 0.0053 | 1.1581 | 3200 | 4.8224 | 0.0133 | 14.4143 |
| 0.0041 | 1.4476 | 4000 | 4.0206 | 0.0121 | 12.9768 |
| 0.0023 | 1.7371 | 4800 | 3.7118 | 0.0116 | 11.9643 |
| 0.0022 | 2.0268 | 5600 | 4.0467 | 0.0125 | 12.7101 |
| 0.002 | 2.3163 | 6400 | 3.7803 | 0.0125 | 12.1962 |
| 0.0016 | 2.6058 | 7200 | 3.7763 | 0.0124 | 12.2696 |
| 0.0018 | 2.8952 | 8000 | 3.6627 | 0.0122 | 12.0570 |
| 0.0013 | 3.1849 | 8800 | 0.0126 | 12.0957 | 3.6893 |
| 0.0015 | 3.4744 | 9600 | 0.0126 | 12.2232 | 3.6893 |
| 0.0013 | 3.7639 | 10400 | 0.0124 | 11.8561 | 3.6023 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0