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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_15_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-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: 54.71511888739345
---
<!-- 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-53-br
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co./facebook/wav2vec2-large-xlsr-53) on the common_voice_15_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7879
- Wer: 54.7151
- Cer: 19.2493
## 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: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 300
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 6.3257 | 2.18 | 500 | 3.0700 | 100.0 | 99.0871 |
| 2.2071 | 4.36 | 1000 | 1.1541 | 80.0449 | 29.4230 |
| 1.0019 | 6.54 | 1500 | 0.8986 | 69.2059 | 24.3938 |
| 0.7796 | 8.71 | 2000 | 0.8015 | 63.3737 | 22.1296 |
| 0.6677 | 10.89 | 2500 | 0.8014 | 61.4984 | 21.4568 |
| 0.5937 | 13.07 | 3000 | 0.7623 | 58.9323 | 20.4929 |
| 0.5454 | 15.25 | 3500 | 0.7975 | 57.8466 | 20.2585 |
| 0.5075 | 17.43 | 4000 | 0.7831 | 56.7250 | 19.7879 |
| 0.4837 | 19.61 | 4500 | 0.7902 | 55.9623 | 19.5101 |
| 0.4529 | 21.79 | 5000 | 0.7851 | 54.9753 | 19.0924 |
| 0.4381 | 23.97 | 5500 | 0.7865 | 55.1727 | 19.3211 |
| 0.4208 | 26.14 | 6000 | 0.8168 | 55.1817 | 19.3967 |
| 0.4197 | 28.32 | 6500 | 0.7879 | 54.7151 | 19.2493 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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