---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- MohamedRashad/arabic-english-code-switching
metrics:
- wer
model-index:
- name: Whisper Large ArabicEnglish - Mostafa Khedr
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: arabic-english-code-switching
      type: MohamedRashad/arabic-english-code-switching
    metrics:
    - name: Wer
      type: wer
      value: 31.61836083760921
---

<!-- 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 Large ArabicEnglish - Mostafa Khedr

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the arabic-english-code-switching dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7108
- Wer: 31.6184

## 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: 16
- seed: 42
- optimizer: Use OptimizerNames.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
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.558         | 0.6748 | 1000  | 0.5802          | 46.1378 |
| 0.3725        | 1.3495 | 2000  | 0.5258          | 43.1008 |
| 0.2131        | 2.0243 | 3000  | 0.5152          | 34.4890 |
| 0.204         | 2.6991 | 4000  | 0.5111          | 37.8727 |
| 0.1012        | 3.3738 | 5000  | 0.5475          | 34.1839 |
| 0.0593        | 4.0486 | 6000  | 0.5693          | 33.2686 |
| 0.0436        | 4.7233 | 7000  | 0.5895          | 33.0190 |
| 0.0189        | 5.3981 | 8000  | 0.6472          | 31.9235 |
| 0.0063        | 6.0729 | 9000  | 0.6850          | 32.2701 |
| 0.0046        | 6.7476 | 10000 | 0.7108          | 31.6184 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3