---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
language:
- pt
license: apache-2.0
metrics:
- wer
tags:
- whisper-event
- generated_from_trainer
model-index:
- name: Whisper Small Mixed-Portuguese
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0 pt
      type: mozilla-foundation/common_voice_17_0
      config: pt
      split: test
      args: pt
    metrics:
    - type: wer
      value: 10.634930784232232
      name: Wer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: pt_br
      split: test
    metrics:
    - type: wer
      value: 8.15
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: facebook/multilingual_librispeech
      type: facebook/multilingual_librispeech
      config: portuguese
      split: test
    metrics:
    - type: wer
      value: 9.69
      name: WER
pipeline_tag: automatic-speech-recognition
---

<!-- 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 Mixed-Portuguese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the pt datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech

It achieves the following results on the evaluation set:
- Loss: 0.2000
- Wer: 10.6349

## 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: 64
- eval_batch_size: 8
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1575        | 0.2   | 1000 | 0.2125          | 12.1855 |
| 0.1986        | 0.4   | 2000 | 0.2062          | 11.5701 |
| 0.0942        | 1.131 | 3000 | 0.1979          | 11.0154 |
| 0.0577        | 1.331 | 4000 | 0.2000          | 10.6349 |
| 0.0516        | 2.062 | 5000 | 0.2007          | 10.6701 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1