---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-small-fa
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: fa
      split: test
      args: fa
    metrics:
    - name: Wer
      type: wer
      value: 35.00088651273169
---

<!-- 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-small-fa

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: 1.3028
- Wer: 35.0009

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step   | Validation Loss | Wer     |
|:-------------:|:--------:|:------:|:---------------:|:-------:|
| 0.0053        | 40.5515  | 100000 | 0.8333          | 36.2993 |
| 0.0011        | 81.1030  | 200000 | 1.0030          | 35.9242 |
| 0.0008        | 121.6545 | 300000 | 1.0865          | 35.6501 |
| 0.0           | 162.2060 | 400000 | 1.1741          | 35.4823 |
| 0.0           | 202.7575 | 500000 | 1.3028          | 35.0009 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1