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---
language:
- ar
license: apache-2.0
base_model: uaepro/whisper-small-ar-2
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Small ar - majed test
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.0
type: mozilla-foundation/common_voice_16_0
config: ar
split: test
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 168.22177271055537
---
<!-- 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 Small ar - majed test
This model is a fine-tuned version of [uaepro/whisper-small-ar-2](https://huggingface.co/uaepro/whisper-small-ar-2) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3392
- Wer: 168.2218
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1459 | 0.41 | 1000 | 0.3714 | 182.4752 |
| 0.1378 | 0.82 | 2000 | 0.3486 | 177.9993 |
| 0.0738 | 1.24 | 3000 | 0.3513 | 184.2939 |
| 0.0855 | 1.65 | 4000 | 0.3392 | 168.2218 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
|