---
library_name: transformers
language:
- fa
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_15_0
metrics:
- wer
model-index:
- name: Whisper large fa - marziye-A
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 15.0
      type: mozilla-foundation/common_voice_15_0
      config: fa
      split: None
      args: 'config: fa, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 19.74175831429967
---

<!-- 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 - marziye-A

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 15.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1571
- Wer: 19.7418

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2189        | 0.1567 | 2000  | 0.2248          | 29.0575 |
| 0.1972        | 0.3134 | 4000  | 0.2035          | 25.1376 |
| 0.1906        | 0.4701 | 6000  | 0.1923          | 25.7159 |
| 0.1595        | 0.6268 | 8000  | 0.1806          | 22.4166 |
| 0.1747        | 0.7835 | 10000 | 0.1753          | 23.0041 |
| 0.1744        | 0.9402 | 12000 | 0.1709          | 22.4932 |
| 0.1357        | 1.0969 | 14000 | 0.1687          | 20.7782 |
| 0.1345        | 1.2536 | 16000 | 0.1646          | 21.3221 |
| 0.1362        | 1.4103 | 18000 | 0.1619          | 21.1082 |
| 0.121         | 1.5670 | 20000 | 0.1601          | 20.3781 |
| 0.1354        | 1.7237 | 22000 | 0.1587          | 19.8157 |
| 0.122         | 1.8804 | 24000 | 0.1571          | 19.7418 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1