|
|
--- |
|
|
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: [] |
|
|
--- |
|
|
|
|
|
<!-- 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 - BH |
|
|
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.0148 |
|
|
- Wer: 0.0829 |
|
|
- Cer: 0.0324 |
|
|
|
|
|
## 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: 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 | 157 | 0.0086 | 0.0889 | 0.0338 | |
|
|
| 0.0069 | 2.0 | 314 | 0.0084 | 0.0896 | 0.0353 | |
|
|
| 0.0042 | 3.0 | 471 | 0.0102 | 0.1070 | 0.0380 | |
|
|
| 0.004 | 4.0 | 628 | 0.0111 | 0.1135 | 0.0406 | |
|
|
| 0.0029 | 5.0 | 785 | 0.0118 | 0.1086 | 0.0401 | |
|
|
| 0.0023 | 6.0 | 942 | 0.0128 | 0.1082 | 0.0388 | |
|
|
| 0.0017 | 7.0 | 1099 | 0.0125 | 0.1033 | 0.0375 | |
|
|
| 0.0013 | 8.0 | 1256 | 0.0133 | 0.1073 | 0.0383 | |
|
|
| 0.0009 | 9.0 | 1413 | 0.0133 | 0.1084 | 0.0376 | |
|
|
| 0.0007 | 10.0 | 1570 | 0.0134 | 0.1024 | 0.0375 | |
|
|
| 0.0005 | 11.0 | 1727 | 0.0142 | 0.1024 | 0.0358 | |
|
|
| 0.0004 | 12.0 | 1884 | 0.0132 | 0.0988 | 0.0331 | |
|
|
| 0.0003 | 13.0 | 2041 | 0.0137 | 0.0952 | 0.0337 | |
|
|
| 0.0001 | 14.0 | 2198 | 0.0144 | 0.0972 | 0.0350 | |
|
|
| 0.0001 | 15.0 | 2355 | 0.0135 | 0.0927 | 0.0338 | |
|
|
| 0.0 | 16.0 | 2512 | 0.0136 | 0.0934 | 0.0339 | |
|
|
| 0.0 | 17.0 | 2669 | 0.0134 | 0.0871 | 0.0313 | |
|
|
| 0.0 | 18.0 | 2826 | 0.0134 | 0.0833 | 0.0307 | |
|
|
| 0.0 | 19.0 | 2983 | 0.0145 | 0.0841 | 0.0358 | |
|
|
| 0.0 | 19.8768 | 3120 | 0.0139 | 0.0782 | 0.0296 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.47.0 |
|
|
- Pytorch 2.5.1+cu121 |
|
|
- Datasets 3.2.0 |
|
|
- Tokenizers 0.21.0 |
|
|
|
