---
library_name: transformers
language:
- fa
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_20_0
metrics:
- wer
model-index:
- name: whisper-base-fa - Sadegh Karimi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 20.0
      type: mozilla-foundation/common_voice_20_0
      args: 'config: fa, split: train, test'
    metrics:
    - name: Wer
      type: wer
      value: 24.311028175747577
---

<!-- 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-base-fa - Sadegh Karimi

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 20.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1949
- Wer: 24.3110

## 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: 8
- seed: 42
- 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: 500
- training_steps: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.524         | 0.0493 | 1000  | 0.5244          | 54.4099 |
| 0.4158        | 0.0986 | 2000  | 0.4063          | 45.3387 |
| 0.3568        | 0.1479 | 3000  | 0.3515          | 39.9380 |
| 0.3243        | 0.1972 | 4000  | 0.3176          | 36.2121 |
| 0.2978        | 0.2465 | 5000  | 0.2894          | 34.1671 |
| 0.2703        | 0.2958 | 6000  | 0.2691          | 32.6126 |
| 0.2591        | 0.3451 | 7000  | 0.2522          | 30.4674 |
| 0.2728        | 0.3944 | 8000  | 0.2388          | 29.0826 |
| 0.2299        | 0.4437 | 9000  | 0.2297          | 27.9737 |
| 0.2368        | 0.4930 | 10000 | 0.2186          | 26.9358 |
| 0.1997        | 0.5423 | 11000 | 0.2116          | 26.3267 |
| 0.2082        | 0.5916 | 12000 | 0.2052          | 25.6820 |
| 0.2131        | 0.6409 | 13000 | 0.2000          | 25.1361 |
| 0.1955        | 0.6902 | 14000 | 0.1966          | 24.4390 |
| 0.1945        | 0.7395 | 15000 | 0.1949          | 24.3110 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.1.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0