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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-common-voice-17_0_vi
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: vi
split: None
args: vi
metrics:
- type: wer
value: 0.43487928843710294
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-17_0_vi
This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7992
- Wer: 0.4349
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.261 | 4.3103 | 500 | 0.4182 | 0.3492 |
| 0.2061 | 8.6207 | 1000 | 0.5416 | 0.4044 |
| 0.1883 | 12.9310 | 1500 | 0.6796 | 0.4304 |
| 0.1336 | 17.2414 | 2000 | 0.8089 | 0.4378 |
| 0.1257 | 21.5517 | 2500 | 0.8244 | 0.4426 |
| 0.098 | 25.8621 | 3000 | 0.7992 | 0.4349 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|