---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper_small-fa_v02
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 fa
      type: mozilla-foundation/common_voice_11_0
      config: fa
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 30.9315
language:
- fa
---

<!-- 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-fa_v02

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 fa dataset. We also did data augmentation using audiomentations library.
It achieves the following results on the evaluation set:
- Loss: 0.2291
- Wer: 30.3423

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure
You can Find the notebooks [here](https://github.com/mohammadh128/Persian_ASR).

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results
| Step | Training Loss | Validation Loss | Wer     |
|:----:|:-------------:|:---------------:|:-------:|
| 500  | 1.770700      | 0.476709        | 52.29181|
| 1000 | 0.762300      | 0.368512        | 41.83410|
| 1500 | 0.645000      | 0.323680        | 37.57881|
| 2000 | 0.601900      | 0.297370        | 36.43209|
| 2500 | 0.529700      | 0.276422        | 33.52608|
| 3000 | 0.523200      | 0.260825        | 31.94485|
| 3500 | 0.488400      | 0.249957        | 33.11771|
| 4000 | 0.464800      | 0.241462        | 30.34238|
| 4500 | 0.440500      | 0.233215        | 31.04969|
| 5000 | 0.440500      | 0.229116        | 30.73605|

### Framework versions

- Transformers 4.26.0
- Pytorch 2.0.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.3