---
language:
- fa
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper small Persian
  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: null
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 32.89950864725314
---

<!-- 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

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.
It achieves the following results on the evaluation set:
- Loss: 0.4924
- Wer: 39.8995

## 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-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- 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

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5533        | 1.56  | 500  | 0.7044          | 54.5499 |
| 0.3951        | 3.12  | 1000 | 0.5893          | 47.5210 |
| 0.3296        | 4.67  | 1500 | 0.5429          | 42.6451 |
| 0.2662        | 6.23  | 2000 | 0.5223          | 40.6644 |
| 0.2535        | 7.79  | 2500 | 0.5045          | 38.5304 |
| 0.224         | 9.35  | 3000 | 0.5002          | 36.8822 |
| 0.2204        | 10.9  | 3500 | 0.4967          | 35.3076 |
| 0.2024        | 12.46 | 4000 | 0.4951          | 34.9883 |
| 0.2099        | 14.02 | 4500 | 0.4921          | 34.9842 |
| 0.1836        | 15.58 | 5000 | 0.4924          | 34.8995 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2