---
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- ymoslem/MediaSpeech
- fixie-ai/common_voice_17_0
- UBC-NLP/Casablanca
- google/fleurs
- deepdml/Tunisian_MSA
metrics:
- wer
model-index:
- name: Whisper Base ar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: ymoslem/MediaSpeech
    metrics:
    - name: Wer
      type: wer
      value: 45.035897247571654
---

<!-- 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 Base ar

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5226
- Wer: 45.0359
- Cer: 14.7675

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- training_steps: 8000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.6613        | 0.125  | 1000 | 0.6130          | 53.4217 | 18.1546 |
| 0.3701        | 0.25   | 2000 | 0.5791          | 50.5885 | 17.1229 |
| 0.1948        | 0.375  | 3000 | 0.5610          | 49.0241 | 16.4269 |
| 0.1173        | 0.5    | 4000 | 0.5481          | 47.8526 | 16.0193 |
| 0.089         | 0.625  | 5000 | 0.5337          | 47.0171 | 15.6262 |
| 0.0606        | 0.75   | 6000 | 0.5255          | 45.5317 | 15.0271 |
| 0.046         | 1.0442 | 7000 | 0.5235          | 45.1791 | 14.8553 |
| 0.0458        | 1.1692 | 8000 | 0.5226          | 45.0359 | 14.7675 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1