---
language:
- pt
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small pt
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: pt
      split: test
      args: pt
    metrics:
    - type: wer
      value: 11.034559928386457
      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: 10.68
      name: WER
---

<!-- 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 pt

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: 0.3836
- Wer: 11.0346

## 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

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.1139        | 2.0325  | 1000 | 0.2474          | 10.7516 |
| 0.024         | 4.0650  | 2000 | 0.2882          | 10.7692 |
| 0.0065        | 6.0976  | 3000 | 0.3367          | 11.0889 |
| 0.0028        | 8.1301  | 4000 | 0.3731          | 11.0362 |
| 0.0023        | 10.1626 | 5000 | 0.3836          | 11.0346 |


### Framework versions

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