---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- deepdml/Tunisian_MSA
- UBC-NLP/Casablanca
- fixie-ai/common_voice_17_0
- google/fleurs
- pain/MASC
- ymoslem/MediaSpeech
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: deepdml/Tunisian_MSA
    metrics:
    - name: Wer
      type: wer
      value: 39.07383265088779
---

<!-- 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: 0.4415
- Wer: 39.0738
- Cer: 12.5149

## 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     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
| 0.7722        | 0.0556 | 1000  | 0.6243          | 54.6887 | 19.2051 |
| 0.4875        | 0.1111 | 2000  | 0.5574          | 49.7126 | 16.7685 |
| 0.2778        | 0.1667 | 3000  | 0.5361          | 47.8269 | 15.8165 |
| 0.1987        | 0.2222 | 4000  | 0.5172          | 45.5776 | 14.8800 |
| 0.1477        | 0.2778 | 5000  | 0.5015          | 45.5666 | 14.9556 |
| 0.1382        | 0.3333 | 6000  | 0.4788          | 43.4751 | 14.1194 |
| 0.0871        | 0.3889 | 7000  | 0.4689          | 42.8049 | 13.8911 |
| 0.0769        | 0.4444 | 8000  | 0.4575          | 41.8777 | 13.6289 |
| 0.082         | 0.5    | 9000  | 0.4542          | 41.3801 | 13.3983 |
| 0.0873        | 0.5556 | 10000 | 0.4483          | 41.4700 | 13.3972 |
| 0.0654        | 0.6111 | 11000 | 0.4399          | 40.4179 | 13.1265 |
| 0.0537        | 0.6667 | 12000 | 0.4434          | 40.2380 | 12.9609 |
| 0.0806        | 0.7222 | 13000 | 0.4402          | 40.1296 | 12.9885 |
| 0.0678        | 0.7778 | 14000 | 0.4363          | 39.9589 | 12.8484 |
| 0.064         | 0.8333 | 15000 | 0.4333          | 39.5476 | 12.7333 |
| 0.0515        | 0.8889 | 16000 | 0.4360          | 38.8939 | 12.5456 |
| 0.0725        | 0.9444 | 17000 | 0.4386          | 39.0793 | 12.6691 |
| 0.0654        | 1.0    | 18000 | 0.4415          | 39.0738 | 12.5149 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.0