---
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 Large 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: 4.816664144852979
    - name: CER
      type: cer
      value: 1.6052355927195898
---

# Whisper Large Portuguese

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on Portuguese using the train and validation splits of [Common Voice 11](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0). Not all validation split data were used during training, I extracted 1k samples from the validation split to be used for evaluation during fine-tuning. When using this model, make sure that your speech input is sampled at 16kHz.


## Usage

```python

from transformers import pipeline

transcriber = pipeline(
  "automatic-speech-recognition", 
  model="jonatasgrosman/whisper-large-pt-cv11"
)

transcriber.model.config.forced_decoder_ids = (
  transcriber.tokenizer.get_decoder_prompt_ids(
    language="pt" 
    task="transcribe"
  )
)

transcription = transcriber("path/to/my_audio.wav")

```

## Evaluation

### Common Voice 11

| | CER | WER |
| --- | --- | --- |
| [jonatasgrosman/whisper-large-pt-cv11](https://huggingface.co/jonatasgrosman/whisper-large-pt-cv11) | 2.52 | 9.56 |
| [jonatasgrosman/whisper-large-pt-cv11](https://huggingface.co/jonatasgrosman/whisper-large-pt-cv11) + text normalization | 1.60 | 4.82 |
| [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) | 4.32 | 13.92 |
| [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) + text normalization | 2.84 | 7.02 |

### Fleurs

| | CER | WER |
| --- | --- | --- |
| [jonatasgrosman/whisper-large-pt-cv11](https://huggingface.co/jonatasgrosman/whisper-large-pt-cv11) | 4.88 | 12.08 |
| [jonatasgrosman/whisper-large-pt-cv11](https://huggingface.co/jonatasgrosman/whisper-large-pt-cv11) + text normalization | 5.46 | 8.57 |
| [jonatasgrosman/whisper-large-pt-cv11](https://huggingface.co/jonatasgrosman/whisper-large-pt-cv11) + text normalization + removal of samples with numbers | 3.36 | 6.05 |
| [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) | 3.52 | 10.55 |
| [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) + text normalization | 4.19 | 7.04 |
| [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) + text normalization + removal of samples with numbers | 3.56 | 6.15 |