---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-small-dar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0 ar
      type: mozilla-foundation/common_voice_17_0
      config: ar
      split: None
      args: ar
    metrics:
    - name: Wer
      type: wer
      value: 0.3367421033522934
---

<!-- 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-dar

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the mozilla-foundation/common_voice_17_0 ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1813
- Wer: 0.3367

## 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: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.303         | 0.5935 | 200  | 0.2434          | 0.4226 |
| 0.2           | 1.1869 | 400  | 0.2035          | 0.3914 |
| 0.1633        | 1.7804 | 600  | 0.1876          | 0.3469 |
| 0.106         | 2.3739 | 800  | 0.1850          | 0.3488 |
| 0.1005        | 2.9674 | 1000 | 0.1813          | 0.3367 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0