---
library_name: transformers
license: apache-2.0
base_model: lgris/bp400-xlsr
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-tutorial-pt-br-5.0
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: pt
      split: None
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 0.7539496503496502
---

<!-- 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. -->

# wav2vec2-large-xlsr-tutorial-pt-br-5.0

This model is a fine-tuned version of [lgris/bp400-xlsr](https://huggingface.co/lgris/bp400-xlsr) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6661
- Wer: 0.7539

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 16

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.0104        | 6.3492  | 200  | 1.2945          | 0.9866 |
| 0.7801        | 12.6984 | 400  | 0.6661          | 0.7539 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1.dev0
- Tokenizers 0.20.0