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---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- MightyStudent/Egyptian-ASR-MGB-3
metrics:
- wer
model-index:
- name: 'Egyptian Whisper Small '
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Egyptian-ASR-MGB-3
type: MightyStudent/Egyptian-ASR-MGB-3
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 46.28931679572398
---
<!-- 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. -->
# Egyptian Whisper Small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Egyptian-ASR-MGB-3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9939
- Wer: 46.2893
## 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: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.4615 | 6.8966 | 100 | 0.6496 | 48.0162 |
| 0.072 | 13.7931 | 200 | 0.7459 | 46.3990 |
| 0.0122 | 20.6897 | 300 | 0.8380 | 45.6863 |
| 0.0054 | 27.5862 | 400 | 0.8981 | 45.0764 |
| 0.0033 | 34.4828 | 500 | 0.9322 | 45.2820 |
| 0.0025 | 41.3793 | 600 | 0.9555 | 45.4670 |
| 0.002 | 48.2759 | 700 | 0.9724 | 46.1454 |
| 0.0017 | 55.1724 | 800 | 0.9843 | 45.9467 |
| 0.0016 | 62.0690 | 900 | 0.9916 | 46.0769 |
| 0.0015 | 68.9655 | 1000 | 0.9939 | 46.2893 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1
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