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---
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
|