|
--- |
|
license: cc-by-nc-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_11_0 |
|
metrics: |
|
- wer |
|
base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h |
|
model-index: |
|
- name: model_weight |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: common_voice_11_0 |
|
type: common_voice_11_0 |
|
config: vi |
|
split: None |
|
args: vi |
|
metrics: |
|
- type: wer |
|
value: 0.14013683555810727 |
|
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. --> |
|
|
|
# model_weight |
|
|
|
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_11_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1765 |
|
- Wer: 0.1401 |
|
|
|
## 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: 32 |
|
- 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: 40 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-------:|:-----:|:---------------:|:------:| |
|
| 15.0719 | 1.3928 | 500 | 4.8260 | 1.0 | |
|
| 4.4273 | 2.7855 | 1000 | 4.6865 | 0.9991 | |
|
| 3.9296 | 4.1783 | 1500 | 4.2965 | 0.9992 | |
|
| 3.4964 | 5.5710 | 2000 | 2.6642 | 0.9583 | |
|
| 2.8184 | 6.9638 | 2500 | 1.7146 | 0.8718 | |
|
| 2.132 | 8.3565 | 3000 | 1.4549 | 0.7103 | |
|
| 1.7481 | 9.7493 | 3500 | 0.9072 | 0.5730 | |
|
| 1.5776 | 11.1421 | 4000 | 0.7414 | 0.5132 | |
|
| 1.3743 | 12.5348 | 4500 | 0.6621 | 0.4089 | |
|
| 1.2417 | 13.9276 | 5000 | 0.4884 | 0.3854 | |
|
| 1.1375 | 15.3203 | 5500 | 0.3561 | 0.3123 | |
|
| 1.0412 | 16.7131 | 6000 | 0.3344 | 0.2945 | |
|
| 0.981 | 18.1058 | 6500 | 0.3063 | 0.2667 | |
|
| 0.9913 | 19.4986 | 7000 | 0.2778 | 0.2244 | |
|
| 0.861 | 20.8914 | 7500 | 0.2511 | 0.2170 | |
|
| 0.8314 | 22.2841 | 8000 | 0.2498 | 0.2127 | |
|
| 0.8669 | 23.6769 | 8500 | 0.2452 | 0.2048 | |
|
| 0.8003 | 25.0696 | 9000 | 0.2251 | 0.1830 | |
|
| 0.7409 | 26.4624 | 9500 | 0.2292 | 0.1820 | |
|
| 0.7282 | 27.8552 | 10000 | 0.2130 | 0.1681 | |
|
| 0.7675 | 29.2479 | 10500 | 0.2290 | 0.1796 | |
|
| 0.7295 | 30.6407 | 11000 | 0.1971 | 0.1617 | |
|
| 0.6308 | 32.0334 | 11500 | 0.2032 | 0.1555 | |
|
| 0.6251 | 33.4262 | 12000 | 0.1905 | 0.1515 | |
|
| 0.5887 | 34.8189 | 12500 | 0.1844 | 0.1481 | |
|
| 0.6642 | 36.2117 | 13000 | 0.1796 | 0.1444 | |
|
| 0.6068 | 37.6045 | 13500 | 0.1808 | 0.1417 | |
|
| 0.5862 | 38.9972 | 14000 | 0.1765 | 0.1401 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
