---
language:
- pt
license: cc-by-4.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny PT
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: pt
      split: test
      args: pt
    metrics:
    - type: wer
      value: 29.11
      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: 26.36
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_9_0
      type: mozilla-foundation/common_voice_9_0
      config: pt
      split: test
    metrics:
    - type: wer
      value: 28.68
      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 Tiny PT

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6077
- Wer: 29.9844

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4143        | 1.04  | 500  | 0.5325          | 32.7399 |
| 0.2693        | 3.03  | 1000 | 0.4718          | 29.4867 |
| 0.1724        | 5.01  | 1500 | 0.4758          | 28.7218 |
| 0.0849        | 7.0   | 2000 | 0.5070          | 29.2211 |
| 0.0659        | 8.04  | 2500 | 0.5223          | 29.3169 |
| 0.0539        | 10.03 | 3000 | 0.5402          | 30.1458 |
| 0.0376        | 12.02 | 3500 | 0.5755          | 29.9995 |
| 0.0217        | 14.0  | 4000 | 0.6067          | 29.6565 |
| 0.0168        | 15.04 | 4500 | 0.6082          | 29.8162 |
| 0.0205        | 17.03 | 5000 | 0.6077          | 29.9844 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2