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---
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: 0.3726759841005257
---
<!-- 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/p3skrhqk)
# 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: 0.7912
- Wer: 0.3727
## 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: cosine
- lr_scheduler_warmup_steps: 400
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8168 | 2.0 | 292 | 3.6240 | 1.0 |
| 3.4344 | 4.0 | 584 | 3.4785 | 1.0 |
| 3.0271 | 6.0 | 876 | 1.8947 | 0.9142 |
| 1.2453 | 8.0 | 1168 | 1.0293 | 0.6091 |
| 0.7876 | 10.0 | 1460 | 0.8472 | 0.5229 |
| 0.6062 | 12.0 | 1752 | 0.7675 | 0.4748 |
| 0.4929 | 14.0 | 2044 | 0.7494 | 0.4303 |
| 0.4376 | 16.0 | 2336 | 0.7481 | 0.4063 |
| 0.3523 | 18.0 | 2628 | 0.7580 | 0.4007 |
| 0.309 | 20.0 | 2920 | 0.7676 | 0.3851 |
| 0.2694 | 22.0 | 3212 | 0.7631 | 0.3819 |
| 0.2531 | 24.0 | 3504 | 0.7717 | 0.3761 |
| 0.2472 | 26.0 | 3796 | 0.7825 | 0.3710 |
| 0.2223 | 28.0 | 4088 | 0.7905 | 0.3732 |
| 0.2183 | 30.0 | 4380 | 0.7912 | 0.3727 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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