---
library_name: transformers
language:
- ar
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper
- egyptian-arabic
- translation
- code-switching
- generated_from_trainer
datasets:
- Assemgamal955/egyptian-english-translation
metrics:
- bleu
model-index:
- name: Whisper Medium Egyptian Arabic --> english Translation
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Assemgamal955/egyptian-english-translation
      type: Assemgamal955/egyptian-english-translation
    metrics:
    - name: Bleu
      type: bleu
      value: 17.93015613103953
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Medium Egyptian Arabic --> english Translation

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Assemgamal955/egyptian-english-translation dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0574
- Model Preparation Time: 0.0101
- Bleu: 17.9302

## 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: 7e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:-------:|
| 1.3837        | 1.0   | 1250 | 1.0422          | 0.0101                 | 21.3456 |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2