|
--- |
|
license: cc-by-nc-4.0 |
|
base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_17_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-common-voice-17_0_vi |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: common_voice_17_0 |
|
type: common_voice_17_0 |
|
config: vi |
|
split: None |
|
args: vi |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.43487928843710294 |
|
--- |
|
|
|
<!-- 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 |
|
|