---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-google-fleurs-pt-br
  results: []
---

<!-- 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-base-google-fleurs-pt-br

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4063
- Wer: 21.6112
- Wer Normalized: 18.0010

## 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: 2.05e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 80
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Wer Normalized |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------:|
| 0.6738        | 0.5   | 100  | 0.3943          | 21.7334 | 17.9487        |
| 0.4816        | 1.01  | 200  | 0.3762          | 20.9203 | 17.1352        |
| 0.2652        | 1.51  | 300  | 0.3872          | 21.1882 | 17.2827        |
| 0.2901        | 2.01  | 400  | 0.3912          | 21.4608 | 17.7061        |
| 0.1408        | 2.51  | 500  | 0.4063          | 21.6112 | 18.0010        |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0