|
--- |
|
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: 0.0097 |
|
- Wer: 0.0951 |
|
- Cer: 0.0412 |
|
|
|
## 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: 5e-06 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 0.0078 | 1.0 | 313 | 0.0073 | 0.0916 | 0.0336 | |
|
| 0.0059 | 2.0 | 626 | 0.0071 | 0.0878 | 0.0325 | |
|
| 0.0051 | 3.0 | 939 | 0.0072 | 0.0878 | 0.0331 | |
|
| 0.0036 | 4.0 | 1252 | 0.0077 | 0.0874 | 0.0336 | |
|
| 0.0017 | 5.0 | 1565 | 0.0081 | 0.0881 | 0.0341 | |
|
| 0.0018 | 6.0 | 1878 | 0.0086 | 0.0871 | 0.0357 | |
|
| 0.0016 | 7.0 | 2191 | 0.0091 | 0.0909 | 0.0369 | |
|
| 0.0016 | 8.0 | 2504 | 0.0095 | 0.0842 | 0.0327 | |
|
| 0.0011 | 9.0 | 2817 | 0.0098 | 0.0889 | 0.0336 | |
|
| 0.001 | 10.0 | 3130 | 0.0102 | 0.0872 | 0.0415 | |
|
| 0.0008 | 11.0 | 3443 | 0.0104 | 0.0865 | 0.0321 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.0 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
