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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: wav2vec2-common-voice-16_1_vi
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_16_1
type: common_voice_16_1
config: vi
split: None
args: vi
metrics:
- type: wer
value: 0.8006303375355835
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. -->
# wav2vec2-common-voice-16_1_vi
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_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4738
- Wer: 0.8006
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 17.2554 | 4.24 | 500 | 3.5535 | 1.0 |
| 3.4431 | 8.47 | 1000 | 3.3988 | 1.0 |
| 2.4492 | 12.71 | 1500 | 1.7446 | 1.0539 |
| 0.9214 | 16.95 | 2000 | 1.4497 | 0.8814 |
| 0.5148 | 21.19 | 2500 | 1.4543 | 0.8333 |
| 0.3619 | 25.42 | 3000 | 1.4791 | 0.8121 |
| 0.3003 | 29.66 | 3500 | 1.4738 | 0.8006 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|