---
license: apache-2.0
base_model: arun100/whisper-base-ar-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Arabic Derived
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs ar_eg
      type: google/fleurs
      config: ar_eg
      split: test
      args: ar_eg
    metrics:
    - name: Wer
      type: wer
      value: 44.287968920723564
---

<!-- 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 Arabic Derived

This model is a fine-tuned version of [arun100/whisper-base-ar-1](https://huggingface.co/arun100/whisper-base-ar-1) on the google/fleurs ar_eg dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6670
- Wer: 44.2880

## 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-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5692        | 52.63  | 500  | 0.6253          | 54.7894 |
| 0.3447        | 105.26 | 1000 | 0.6001          | 45.2106 |
| 0.2067        | 157.89 | 1500 | 0.6109          | 44.7372 |
| 0.1273        | 210.53 | 2000 | 0.6303          | 44.7372 |
| 0.0788        | 263.16 | 2500 | 0.6508          | 44.4579 |
| 0.0526        | 315.79 | 3000 | 0.6670          | 44.2880 |
| 0.0404        | 368.42 | 3500 | 0.6784          | 44.7129 |
| 0.0335        | 421.05 | 4000 | 0.6860          | 46.2668 |
| 0.0296        | 473.68 | 4500 | 0.6907          | 44.5915 |
| 0.0287        | 526.32 | 5000 | 0.6924          | 44.6279 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0