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library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- pain/MASC
- google/fleurs
- deepdml/Tunisian_MSA
- deepdml/mtedx
- ymoslem/MediaSpeech
- UBC-NLP/Casablanca
- fixie-ai/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Tiny ar
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: pain/MASC
metrics:
- name: Wer
type: wer
value: 52.36224086961312
---
<!-- 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 Tiny ar
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5962
- Wer: 52.3622
- Cer: 18.7245
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- training_steps: 18000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
| 1.1234 | 0.0556 | 1000 | 0.8106 | 67.0994 | 25.5658 |
| 0.8957 | 0.1111 | 2000 | 0.7234 | 62.5310 | 23.3911 |
| 0.7114 | 0.1667 | 3000 | 0.6871 | 59.7675 | 21.8722 |
| 0.6346 | 0.2222 | 4000 | 0.6637 | 58.1976 | 20.7336 |
| 0.4961 | 0.2778 | 5000 | 0.6545 | 57.7404 | 20.7048 |
| 0.4354 | 0.3333 | 6000 | 0.6473 | 56.7948 | 20.2061 |
| 0.3924 | 0.3889 | 7000 | 0.6325 | 55.8400 | 20.0139 |
| 0.3466 | 0.4444 | 8000 | 0.6274 | 55.4176 | 20.1441 |
| 0.2979 | 0.5 | 9000 | 0.6206 | 54.6997 | 19.6005 |
| 0.3099 | 0.5556 | 10000 | 0.6150 | 54.0166 | 19.3231 |
| 0.2681 | 0.6111 | 11000 | 0.6120 | 53.5980 | 19.1106 |
| 0.2383 | 0.6667 | 12000 | 0.6113 | 53.5576 | 19.4238 |
| 0.2582 | 0.7222 | 13000 | 0.6060 | 52.7515 | 18.7573 |
| 0.1543 | 0.7778 | 14000 | 0.6018 | 52.6175 | 18.4895 |
| 0.2356 | 0.8333 | 15000 | 0.6023 | 52.9902 | 18.9782 |
| 0.2031 | 0.8889 | 16000 | 0.5984 | 52.5165 | 18.8550 |
| 0.2437 | 0.9444 | 17000 | 0.5951 | 52.4926 | 18.7514 |
| 0.2269 | 1.0 | 18000 | 0.5962 | 52.3622 | 18.7245 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.0
## Citation
Please cite the model using the following BibTeX entry:
```bibtex
@misc{deepdml/whisper-tiny-ar-mix-norm,
title={Fine-tuned Whisper tiny ASR model for speech recognition in Arabic},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-ar-mix-norm}},
year={2026}
}
```
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