---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper base 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 base AR - BH

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text-segments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0231
- Wer: 0.2331

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.017         | 1.3333  | 100  | 0.0233          | 0.2610 |
| 0.0148        | 2.6667  | 200  | 0.0216          | 0.2495 |
| 0.0094        | 4.0     | 300  | 0.0204          | 0.2438 |
| 0.0048        | 5.3333  | 400  | 0.0203          | 0.2409 |
| 0.0027        | 6.6667  | 500  | 0.0206          | 0.2421 |
| 0.0017        | 8.0     | 600  | 0.0213          | 0.2491 |
| 0.0007        | 9.3333  | 700  | 0.0218          | 0.2384 |
| 0.0005        | 10.6667 | 800  | 0.0221          | 0.2368 |
| 0.0003        | 12.0    | 900  | 0.0224          | 0.2372 |
| 0.0003        | 13.3333 | 1000 | 0.0226          | 0.2347 |
| 0.0003        | 14.6667 | 1100 | 0.0228          | 0.2327 |
| 0.0002        | 16.0    | 1200 | 0.0229          | 0.2335 |
| 0.0002        | 17.3333 | 1300 | 0.0230          | 0.2331 |
| 0.0002        | 18.6667 | 1400 | 0.0231          | 0.2331 |
| 0.0002        | 20.0    | 1500 | 0.0231          | 0.2335 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3