---
language:
- fa
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 Persian - Persian ASR
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common-voice-17-0
      type: mozilla-foundation-common-voice-17-0
      config: default
      split: test[:20%]
      args: 'config: Persian, split: train[:20%]+validation[:20%]'
    metrics:
    - name: Wer
      type: wer
      value: 43.69646680942184
---

<!-- 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 Persian - Persian ASR

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common-voice-17-0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6543
- Wer: 43.6965

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3355        | 1.0   | 1973 | 0.5819          | 50.9101 |
| 0.176         | 2.0   | 3946 | 0.5479          | 49.8796 |
| 0.0767        | 3.0   | 5919 | 0.5610          | 45.3292 |
| 0.0262        | 4.0   | 7892 | 0.6115          | 44.0645 |
| 0.0116        | 5.0   | 9865 | 0.6543          | 43.6965 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1