---
library_name: transformers
language:
- fa
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large fa - Mobin Tadbir Sharif
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: fa
      split: None
      args: 'config: fa, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 91.65836687359301
---

<!-- 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 Large fa - Mobin Tadbir Sharif

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8106
- Wer: 91.6584

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer      |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.581         | 0.0869 | 1000  | 2.5843          | 104.8093 |
| 2.2554        | 0.1738 | 2000  | 2.3093          | 111.6202 |
| 2.1214        | 0.2607 | 3000  | 2.1839          | 105.5556 |
| 2.024         | 0.3477 | 4000  | 2.1036          | 113.6312 |
| 1.9005        | 0.4346 | 5000  | 2.0217          | 135.5618 |
| 1.7344        | 0.5215 | 6000  | 1.8019          | 107.0619 |
| 1.4862        | 0.6084 | 7000  | 1.5560          | 101.7136 |
| 1.253         | 0.6953 | 8000  | 1.3641          | 106.0004 |
| 1.0361        | 0.7822 | 9000  | 1.1275          | 98.4010  |
| 0.8509        | 0.8692 | 10000 | 0.9458          | 97.6069  |
| 0.7212        | 0.9561 | 11000 | 0.8106          | 91.6584  |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0