---
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: 0.0206
- Wer: 0.1174
- Cer: 0.0425

## 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: 1e-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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0204        | 1.0   | 250  | 0.0218          | 0.1251 | 0.0425 |
| 0.0116        | 2.0   | 500  | 0.0125          | 0.1298 | 0.0427 |
| 0.0086        | 3.0   | 750  | 0.0116          | 0.1229 | 0.0421 |
| 0.0049        | 4.0   | 1000 | 0.0121          | 0.1227 | 0.0449 |
| 0.0041        | 5.0   | 1250 | 0.0130          | 0.1231 | 0.0415 |
| 0.0029        | 6.0   | 1500 | 0.0143          | 0.1207 | 0.0407 |
| 0.0013        | 7.0   | 1750 | 0.0155          | 0.12   | 0.0390 |
| 0.0018        | 8.0   | 2000 | 0.0165          | 0.1265 | 0.0449 |
| 0.0008        | 9.0   | 2250 | 0.0173          | 0.1245 | 0.0414 |
| 0.0002        | 10.0  | 2500 | 0.0179          | 0.1222 | 0.0406 |
| 0.0002        | 11.0  | 2750 | 0.0182          | 0.1186 | 0.0400 |
| 0.0002        | 12.0  | 3000 | 0.0184          | 0.1198 | 0.0398 |
| 0.0001        | 13.0  | 3250 | 0.0187          | 0.1198 | 0.0404 |
| 0.0001        | 14.0  | 3500 | 0.0206          | 0.1174 | 0.0425 |
| 0.0           | 15.0  | 3750 | 0.0190          | 0.1189 | 0.0399 |


### Framework versions

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