---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-ar-private
  results: []
---

<!-- 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-ar-private

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3115
- Wer: 36.1533

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- training_steps: 10000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.3798        | 0.7855 | 2000  | 0.3634          | 44.2367 |
| 0.2557        | 1.5711 | 4000  | 0.3220          | 39.4150 |
| 0.1723        | 2.3566 | 6000  | 0.3103          | 37.1623 |
| 0.1172        | 3.1422 | 8000  | 0.3125          | 36.7185 |
| 0.113         | 3.9277 | 10000 | 0.3115          | 36.1533 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1