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---
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: 15.646320843094573
---
<!-- 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 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: 1.0455
- Model Preparation Time: 0.0097
- Bleu: 15.6463
## 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: 2e-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: 50
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:-------:|
| 1.6186 | 1.0 | 1563 | 1.0344 | 0.0097 | 16.9977 |
### Framework versions
- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
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