---
license: cc-by-nc-4.0
base_model: utter-project/mHuBERT-147
tags:
- generated_from_trainer
datasets:
- common_voice_15_0
metrics:
- wer
model-index:
- name: mHuBERT-147-br
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_15_0
      type: common_voice_15_0
      config: br
      split: None
      args: br
    metrics:
    - name: Wer
      type: wer
      value: 54.40414507772021
---

<!-- 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. -->

# mHuBERT-147-br

This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_15_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7748
- Wer: 54.4041
- Cer: 18.4091

## 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: 3.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 6.9168        | 2.18  | 1000  | 3.4435          | 100.0   | 99.8848 |
| 2.5187        | 4.36  | 2000  | 1.5458          | 84.7983 | 31.7071 |
| 1.2569        | 6.54  | 3000  | 1.0204          | 75.0740 | 26.1506 |
| 0.9322        | 8.71  | 4000  | 0.8765          | 69.9852 | 24.0654 |
| 0.785         | 10.89 | 5000  | 0.8191          | 66.0252 | 22.4968 |
| 0.6997        | 13.07 | 6000  | 0.8166          | 64.1007 | 21.8478 |
| 0.6318        | 15.25 | 7000  | 0.7961          | 61.4730 | 20.9685 |
| 0.5827        | 17.43 | 8000  | 0.7853          | 59.9926 | 20.2523 |
| 0.5573        | 19.61 | 9000  | 0.7536          | 59.6873 | 20.0737 |
| 0.5173        | 21.79 | 10000 | 0.7525          | 58.3364 | 19.6014 |
| 0.4874        | 23.97 | 11000 | 0.7694          | 57.4759 | 19.4766 |
| 0.4643        | 26.14 | 12000 | 0.7800          | 56.1158 | 19.0984 |
| 0.4511        | 28.32 | 13000 | 0.7640          | 55.6255 | 18.7892 |
| 0.4268        | 30.5  | 14000 | 0.7495          | 55.4404 | 18.6548 |
| 0.423         | 32.68 | 15000 | 0.7641          | 55.0703 | 18.5281 |
| 0.4166        | 34.86 | 16000 | 0.7730          | 54.8020 | 18.5377 |
| 0.3968        | 37.04 | 17000 | 0.7658          | 54.4597 | 18.3995 |
| 0.3958        | 39.22 | 18000 | 0.7748          | 54.4041 | 18.4091 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2