---
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: 0.6283
- Wer: 25.9071

## 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: 2.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 120
- training_steps: 2400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0871        | 2.72  | 400  | 0.4838          | 24.4078 |
| 0.0066        | 5.44  | 800  | 0.5647          | 25.5452 |
| 0.0013        | 8.16  | 1200 | 0.5981          | 25.6110 |
| 0.0008        | 10.88 | 1600 | 0.6143          | 25.6533 |
| 0.0006        | 13.61 | 2000 | 0.6245          | 25.7661 |
| 0.0006        | 16.33 | 2400 | 0.6283          | 25.9071 |


### Framework versions

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