---
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: 6.331942299477541
---

<!-- 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: 0.1753
- Wer: 6.3319

## 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-06
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0999        | 3.52  | 1000  | 0.1753          | 6.3319 |
| 0.0436        | 7.04  | 2000  | 0.2027          | 6.5521 |
| 0.0113        | 10.56 | 3000  | 0.3135          | 6.7361 |
| 0.0041        | 14.08 | 4000  | 0.3616          | 6.8889 |
| 0.0026        | 17.61 | 5000  | 0.3908          | 7.0565 |
| 0.0016        | 21.13 | 6000  | 0.4078          | 7.1419 |
| 0.0013        | 24.65 | 7000  | 0.4227          | 7.1534 |
| 0.001         | 28.17 | 8000  | 0.4343          | 7.1764 |
| 0.0008        | 31.69 | 9000  | 0.4424          | 7.2076 |
| 0.0008        | 35.21 | 10000 | 0.4464          | 7.2224 |


### Framework versions

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