---
language:
- pt
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Portuguese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 pt
      type: mozilla-foundation/common_voice_13_0
      config: pt
      split: test
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 7.115631058390563
---

<!-- 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 Medium Portuguese

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2733
- Wer: 7.1156

## 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: 32
- 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: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0335        | 3.52  | 1000  | 0.2096          | 7.4771 |
| 0.0073        | 7.04  | 2000  | 0.2733          | 7.1156 |
| 0.0049        | 10.56 | 3000  | 0.2880          | 7.2520 |
| 0.0031        | 14.08 | 4000  | 0.3146          | 7.6233 |
| 0.0025        | 17.61 | 5000  | 0.3191          | 7.7416 |
| 0.0012        | 21.13 | 6000  | 0.3269          | 7.7942 |
| 0.0022        | 24.65 | 7000  | 0.3430          | 7.9141 |
| 0.0018        | 28.17 | 8000  | 0.3581          | 8.0242 |
| 0.0007        | 31.69 | 9000  | 0.3701          | 8.1556 |
| 0.001         | 35.21 | 10000 | 0.3582          | 8.0390 |
| 0.0002        | 38.73 | 11000 | 0.3851          | 7.8467 |
| 0.0004        | 42.25 | 12000 | 0.3890          | 8.1622 |
| 0.0001        | 45.77 | 13000 | 0.3757          | 8.0636 |
| 0.0           | 49.3  | 14000 | 0.4009          | 7.8895 |
| 0.0           | 52.82 | 15000 | 0.4136          | 7.8352 |
| 0.0           | 56.34 | 16000 | 0.4231          | 7.8106 |
| 0.0           | 59.86 | 17000 | 0.4311          | 7.7432 |
| 0.0           | 63.38 | 18000 | 0.4380          | 7.7022 |
| 0.0           | 66.9  | 19000 | 0.4430          | 7.6808 |
| 0.0           | 70.42 | 20000 | 0.4452          | 7.6644 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.15.1