---
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: 0.0256
- Wer: 0.1250
- Cer: 0.0445

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0263        | 0.9973  | 187  | 0.0205          | 0.1624 | 0.0613 |
| 0.0093        | 2.0     | 375  | 0.0149          | 0.1519 | 0.0529 |
| 0.0051        | 2.9973  | 562  | 0.0157          | 0.1580 | 0.0512 |
| 0.004         | 4.0     | 750  | 0.0181          | 0.1636 | 0.0539 |
| 0.002         | 4.9973  | 937  | 0.0193          | 0.1557 | 0.0502 |
| 0.0011        | 6.0     | 1125 | 0.0206          | 0.1558 | 0.0506 |
| 0.0009        | 6.9973  | 1312 | 0.0213          | 0.1513 | 0.0498 |
| 0.0005        | 8.0     | 1500 | 0.0214          | 0.1544 | 0.0504 |
| 0.0004        | 8.9973  | 1687 | 0.0220          | 0.1464 | 0.0458 |
| 0.0004        | 10.0    | 1875 | 0.0216          | 0.1459 | 0.0461 |
| 0.0002        | 10.9973 | 2062 | 0.0224          | 0.1452 | 0.0454 |
| 0.0001        | 12.0    | 2250 | 0.0224          | 0.1437 | 0.0452 |
| 0.0001        | 12.9973 | 2437 | 0.0234          | 0.2224 | 0.0832 |
| 0.0           | 14.0    | 2625 | 0.0231          | 0.1356 | 0.0540 |
| 0.0           | 14.9973 | 2812 | 0.0236          | 0.2134 | 0.0797 |
| 0.0           | 16.0    | 3000 | 0.0241          | 0.2159 | 0.0796 |
| 0.0           | 16.9973 | 3187 | 0.0253          | 0.1338 | 0.0517 |
| 0.0           | 18.0    | 3375 | 0.0257          | 0.1271 | 0.0493 |
| 0.0           | 18.9973 | 3562 | 0.0264          | 0.1287 | 0.0492 |
| 0.0           | 19.9467 | 3740 | 0.0266          | 0.1280 | 0.0489 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1