xlsr53-ptbr-3 / README.md
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---
library_name: transformers
license: apache-2.0
base_model: lejonck/xlsr53-ptbr-2
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xlsr53-ptbr-3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: pt
split: None
args: pt
metrics:
- name: Wer
type: wer
value: 0.98989898989899
---
<!-- 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. -->
# xlsr53-ptbr-3
This model is a fine-tuned version of [lejonck/xlsr53-ptbr-2](https://huggingface.co/lejonck/xlsr53-ptbr-2) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7741
- Wer: 0.9899
- Cer: 10.8976
## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 5.1364 | 1.0 | 250 | 4.1358 | 0.9949 | 10.6432 |
| 5.0838 | 2.0 | 500 | 4.0543 | 0.9941 | 10.5248 |
| 4.3622 | 3.0 | 750 | 3.9937 | 0.9924 | 10.2184 |
| 4.1477 | 4.0 | 1000 | 3.9178 | 0.9924 | 10.2848 |
| 4.4121 | 5.0 | 1250 | 3.8755 | 0.9924 | 10.3005 |
| 3.9327 | 6.0 | 1500 | 3.8408 | 0.9907 | 10.4761 |
| 4.0681 | 7.0 | 1750 | 3.8321 | 0.9916 | 10.7547 |
| 3.9356 | 8.0 | 2000 | 3.7912 | 0.9916 | 10.5872 |
| 4.3374 | 9.0 | 2250 | 3.7739 | 0.9899 | 10.6934 |
| 3.7845 | 10.0 | 2500 | 3.7741 | 0.9899 | 10.8360 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0