---
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: 0.0121
- Wer: 13.2495
- Cer: 4.3278

## 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: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Cer     | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:-------:|:---------------:|:--------:|
| 0.0258        | 0.1408 | 400  | 52.2218 | 0.0246          | 104.9348 |
| 0.0177        | 0.2817 | 800  | 10.2633 | 0.0184          | 26.2089  |
| 0.0116        | 0.4225 | 1200 | 7.3210  | 0.0160          | 20.9517  |
| 0.0101        | 0.5633 | 1600 | 5.8227  | 0.0141          | 17.5020  |
| 0.008         | 0.7042 | 2000 | 5.1235  | 0.0127          | 16.3695  |
| 0.0057        | 0.8450 | 2400 | 4.8168  | 0.0119          | 15.2343  |
| 0.0056        | 0.9858 | 2800 | 4.6678  | 0.0116          | 14.6364  |
| 0.0071        | 1.1267 | 3200 | 0.0135  | 15.8929         | 5.3042   |
| 0.0059        | 1.2676 | 3600 | 0.0132  | 15.7165         | 5.0437   |
| 0.0056        | 1.4084 | 4000 | 0.0124  | 14.5758         | 5.3648   |
| 0.0041        | 1.5492 | 4400 | 0.0122  | 14.2259         | 4.7531   |
| 0.0038        | 1.6901 | 4800 | 0.0120  | 13.8043         | 4.7431   |
| 0.004         | 1.8309 | 5200 | 0.0119  | 14.1818         | 4.9569   |
| 0.0036        | 1.9717 | 5600 | 0.0118  | 14.0743         | 4.9171   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0