|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- vivos |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-vivos-asr |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: vivos |
|
type: vivos |
|
config: default |
|
split: None |
|
args: default |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.46064565231179044 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/khackho01125-CMC-University/Wav2Vec2/runs/3iat438k) |
|
# wav2vec2-vivos-asr |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the vivos dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8301 |
|
- Wer: 0.4606 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 400 |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 5.7906 | 2.0 | 292 | 3.6543 | 1.0 | |
|
| 3.4396 | 4.0 | 584 | 3.5033 | 1.0 | |
|
| 3.4081 | 6.0 | 876 | 3.4360 | 1.0 | |
|
| 2.4196 | 8.0 | 1168 | 1.5751 | 0.8002 | |
|
| 1.3285 | 10.0 | 1460 | 1.1699 | 0.6628 | |
|
| 1.0944 | 12.0 | 1752 | 1.0408 | 0.6051 | |
|
| 0.9742 | 14.0 | 2044 | 0.9772 | 0.5657 | |
|
| 0.9219 | 16.0 | 2336 | 0.9344 | 0.5515 | |
|
| 0.817 | 18.0 | 2628 | 0.8871 | 0.5176 | |
|
| 0.7636 | 20.0 | 2920 | 0.8734 | 0.5050 | |
|
| 0.7192 | 22.0 | 3212 | 0.8556 | 0.4909 | |
|
| 0.6904 | 24.0 | 3504 | 0.8471 | 0.4772 | |
|
| 0.6703 | 26.0 | 3796 | 0.8489 | 0.4754 | |
|
| 0.6343 | 28.0 | 4088 | 0.8364 | 0.4689 | |
|
| 0.6161 | 30.0 | 4380 | 0.8301 | 0.4606 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
