---
library_name: transformers
language:
- fa
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- vhdm/persian-voice-v1.1
metrics:
- wer
model-index:
- name: vhdm/whisper-v3-turbo-persian-v1.1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: vhdm/persian-voice-v1
      type: vhdm/persian-voice-v1.1
      args: 'config: fa, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 14.065335753176045
---

<!-- 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. -->

# vhdm/whisper-v3-turbo-persian-v1.1

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the vhdm/persian-voice-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1445
- Wer: 14.0653

## 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 OptimizerNames.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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.219         | 0.6150 | 1000 | 0.2093          | 22.0750 |
| 0.1191        | 1.2300 | 2000 | 0.1698          | 17.8463 |
| 0.1051        | 1.8450 | 3000 | 0.1485          | 15.7895 |
| 0.0644        | 2.4600 | 4000 | 0.1530          | 16.0375 |
| 0.0289        | 3.0750 | 5000 | 0.1445          | 14.0653 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.1+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1