---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
base_model: utter-project/mHuBERT-147
datasets:
- common_voice_15_0
metrics:
- wer
model-index:
- name: mHuBERT-147-br
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_15_0
      type: common_voice_15_0
      config: br
      split: None
      args: br
    metrics:
    - type: wer
      value: 53.76572908956329
      name: Wer
---

<!-- 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: 0.7650
- Wer: 53.7657
- Cer: 18.3841

## 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: 3.7e-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  | Cer     | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|
| 6.5746        | 2.18  | 1000  | 99.8848 | 3.8929          | 100.0   |
| 2.8591        | 4.36  | 2000  | 51.1549 | 1.8873          | 97.5296 |
| 1.4189        | 6.54  | 3000  | 27.4120 | 1.0985          | 77.2853 |
| 0.9787        | 8.71  | 4000  | 0.8995  | 71.3360         | 24.4590 |
| 0.803         | 10.89 | 5000  | 0.8429  | 67.1817         | 22.9902 |
| 0.718         | 13.07 | 6000  | 0.8035  | 63.8879         | 21.6750 |
| 0.6359        | 15.25 | 7000  | 0.7927  | 62.2502         | 21.1144 |
| 0.5832        | 17.43 | 8000  | 0.7508  | 60.3072         | 20.3406 |
| 0.555         | 19.61 | 9000  | 0.7509  | 58.7990         | 19.8568 |
| 0.5167        | 21.79 | 10000 | 0.7757  | 58.0218         | 19.7569 |
| 0.4917        | 23.97 | 11000 | 0.7588  | 56.9671         | 19.4574 |
| 0.4629        | 26.14 | 12000 | 0.7710  | 55.6255         | 19.0792 |
| 0.4454        | 28.32 | 13000 | 0.7546  | 55.0888         | 18.8257 |
| 0.4235        | 30.5  | 14000 | 0.7548  | 54.9963         | 18.7240 |
| 0.4135        | 32.68 | 15000 | 0.7689  | 54.6725         | 18.6222 |
| 0.411         | 34.86 | 16000 | 0.7619  | 54.4504         | 18.5320 |
| 0.3934        | 37.04 | 17000 | 0.7621  | 53.9323         | 18.4014 |
| 0.3912        | 39.22 | 18000 | 0.7650  | 53.7657         | 18.3841 |


### Framework versions

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