---
language:
- pt
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Sussurrar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: pt
      split: test
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 26.260504201680675
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Sussurrar

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4367
- Wer: 26.2605

## Model description

The model is fine-tuned for ASR in Portuguese. We decided to train in Portuguese because it is a very common language, yet does not have many resources in terms of NLP.

## Intended uses & limitations

The model is used for Automatic Speach Recognition. It is fine-tuned in the Portuguese language. 

## Training and evaluation data

Trained and evaluated on the Common Voice 11 Portuguese data.

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4076        | 0.1   | 200  | 0.5182          | 32.4930 |
| 0.3462        | 0.2   | 400  | 0.4912          | 29.0266 |
| 0.3283        | 0.3   | 600  | 0.4671          | 27.0308 |
| 0.3579        | 0.4   | 800  | 0.4662          | 26.6457 |
| 0.2766        | 0.5   | 1000 | 0.4639          | 26.7157 |
| 0.2147        | 1.03  | 1200 | 0.4470          | 26.7857 |
| 0.1877        | 1.13  | 1400 | 0.4382          | 26.4006 |
| 0.192         | 1.23  | 1600 | 0.4430          | 26.3655 |
| 0.1894        | 1.33  | 1800 | 0.4349          | 26.4006 |
| 0.1725        | 1.43  | 2000 | 0.4367          | 26.2605 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2