pytorch tensorboard wav2vec2 automatic-speech-recognition dataset:vivos_dataset transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- vivos_dataset
model-index:
- name: wav2vec2-base-vios
  results: []
---

<!-- 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-base-vios

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the vivos_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3729
- Wer: 0.2427

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.4755        | 1.37  | 500  | 0.7991          | 0.5957 |
| 0.5424        | 2.75  | 1000 | 0.4290          | 0.3653 |
| 0.3586        | 4.12  | 1500 | 0.3809          | 0.2890 |
| 0.2824        | 5.49  | 2000 | 0.3808          | 0.2749 |
| 0.2249        | 6.87  | 2500 | 0.3467          | 0.2389 |
| 0.1745        | 8.24  | 3000 | 0.3688          | 0.2384 |
| 0.1459        | 9.61  | 3500 | 0.3729          | 0.2427 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
