---
library_name: transformers
language:
- fa
license: apache-2.0
base_model: SadeghK/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: 10.468362043705566
---

<!-- 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 [SadeghK/whisper-base](https://huggingface.co/SadeghK/whisper-base) on the Common Voice 20.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0809
- Wer: 10.4684

## 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: 40000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.1234        | 0.0493 | 1000  | 0.1698          | 21.8312 |
| 0.1303        | 0.0986 | 2000  | 0.1663          | 22.9153 |
| 0.1241        | 0.1479 | 3000  | 0.1623          | 20.8843 |
| 0.1223        | 0.1972 | 4000  | 0.1616          | 20.7470 |
| 0.1281        | 0.2465 | 5000  | 0.1522          | 19.3606 |
| 0.1111        | 0.2958 | 6000  | 0.1483          | 20.0901 |
| 0.1097        | 0.3451 | 7000  | 0.1452          | 19.0445 |
| 0.1439        | 0.3944 | 8000  | 0.1367          | 18.0251 |
| 0.1053        | 0.4437 | 9000  | 0.1347          | 17.5902 |
| 0.1248        | 0.4930 | 10000 | 0.1281          | 16.9486 |
| 0.1081        | 0.5423 | 11000 | 0.1252          | 15.9200 |
| 0.1062        | 0.5916 | 12000 | 0.1222          | 15.8167 |
| 0.1139        | 0.6409 | 13000 | 0.1181          | 15.6038 |
| 0.1011        | 0.6902 | 14000 | 0.1145          | 15.0918 |
| 0.098         | 0.7395 | 15000 | 0.1141          | 15.0194 |
| 0.1176        | 0.7888 | 16000 | 0.1091          | 14.1048 |
| 0.0933        | 0.8381 | 17000 | 0.1067          | 13.9028 |
| 0.0981        | 0.8874 | 18000 | 0.1042          | 13.6391 |
| 0.0909        | 0.9367 | 19000 | 0.1012          | 13.2119 |
| 0.0714        | 0.9860 | 20000 | 0.1001          | 13.1826 |
| 0.0491        | 1.0353 | 21000 | 0.0985          | 12.9251 |
| 0.059         | 1.0846 | 22000 | 0.0966          | 12.6799 |
| 0.0492        | 1.1339 | 23000 | 0.0959          | 12.4501 |
| 0.0625        | 1.1832 | 24000 | 0.0943          | 12.5241 |
| 0.0429        | 1.2325 | 25000 | 0.0946          | 12.4424 |
| 0.0403        | 1.2818 | 26000 | 0.0931          | 12.1370 |
| 0.0474        | 1.3311 | 27000 | 0.0921          | 11.7330 |
| 0.0484        | 1.3804 | 28000 | 0.0910          | 11.5710 |
| 0.0585        | 1.4297 | 29000 | 0.0896          | 11.7067 |
| 0.0431        | 1.4790 | 30000 | 0.0890          | 11.3875 |
| 0.045         | 1.5283 | 31000 | 0.0875          | 11.2842 |
| 0.0494        | 1.5776 | 32000 | 0.0862          | 11.5433 |
| 0.0448        | 1.6269 | 33000 | 0.0854          | 11.0282 |
| 0.0508        | 1.6762 | 34000 | 0.0849          | 11.0498 |
| 0.0432        | 1.7255 | 35000 | 0.0837          | 10.7583 |
| 0.0356        | 1.7748 | 36000 | 0.0826          | 10.8339 |
| 0.0353        | 1.8241 | 37000 | 0.0819          | 10.5300 |
| 0.043         | 1.8734 | 38000 | 0.0815          | 10.4838 |
| 0.0434        | 1.9227 | 39000 | 0.0812          | 10.5038 |
| 0.0382        | 1.9720 | 40000 | 0.0809          | 10.4684 |


### Framework versions

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