---
language:
- pt
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny PT with Common Voice 11
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      args: 'config: pt, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 33.24473522796974
---

<!-- 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 with Common Voice 11

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: 0.5205
- Wer: 33.2447

## 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: 8
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 16000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3154        | 0.44  | 1000  | 0.4987          | 36.2196 |
| 0.3252        | 0.88  | 2000  | 0.4586          | 33.6213 |
| 0.1989        | 1.32  | 3000  | 0.4457          | 32.7455 |
| 0.3112        | 1.76  | 4000  | 0.4356          | 31.4097 |
| 0.1329        | 2.2   | 5000  | 0.4348          | 31.1559 |
| 0.1193        | 2.64  | 6000  | 0.4343          | 31.4046 |
| 0.0723        | 3.07  | 7000  | 0.4424          | 31.5869 |
| 0.0698        | 3.51  | 8000  | 0.4497          | 32.0827 |
| 0.0865        | 3.95  | 9000  | 0.4497          | 31.0945 |
| 0.0522        | 4.39  | 10000 | 0.4716          | 32.2190 |
| 0.0542        | 4.83  | 11000 | 0.4761          | 32.6944 |
| 0.061         | 5.27  | 12000 | 0.4983          | 32.0691 |
| 0.0459        | 5.71  | 13000 | 0.4985          | 32.4968 |
| 0.0338        | 6.15  | 14000 | 0.5123          | 33.3129 |
| 0.0492        | 6.59  | 15000 | 0.5217          | 33.2686 |
| 0.0194        | 7.03  | 16000 | 0.5205          | 33.2447 |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1