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---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: 'arabic Whisper Small '
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13.0
type: mozilla-foundation/common_voice_13_0
config: ar
split: test
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 44.40746529373909
---
<!-- 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. -->
# arabic Whisper Small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3384
- Wer: 44.4075
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.3476 | 0.4148 | 1000 | 0.4130 | 52.3435 |
| 0.2522 | 0.8295 | 2000 | 0.3676 | 49.2305 |
| 0.1606 | 1.2443 | 3000 | 0.3475 | 44.8855 |
| 0.161 | 1.6591 | 4000 | 0.3384 | 44.4075 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1
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