---
language:
- pt
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Portuguese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 pt
      type: mozilla-foundation/common_voice_11_0
      config: pt
      split: test
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 14.684129429892142
---

<!-- 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 Portuguese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3056
- Wer: 14.6841
- Cer: 5.8856

## 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: 5e-06
- train_batch_size: 32
- 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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.2817        | 0.92  | 500  | 0.3352          | 15.9476 | 6.3609 |
| 0.2245        | 1.84  | 1000 | 0.3047          | 15.0231 | 5.9326 |
| 0.1587        | 2.76  | 1500 | 0.2985          | 15.0847 | 5.9326 |
| 0.1181        | 3.68  | 2000 | 0.3056          | 14.6841 | 5.8856 |
| 0.0741        | 4.6   | 2500 | 0.3162          | 14.9923 | 5.9906 |
| 0.0438        | 5.52  | 3000 | 0.3466          | 15.4700 | 6.2255 |
| 0.0294        | 6.45  | 3500 | 0.3799          | 15.2234 | 6.1647 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2