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

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# wav2vec2-base-vivos

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4977
- Wer: 0.3249

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3297        | 2.0   | 500  | 2.6466          | 1.0022 |
| 0.895         | 4.0   | 1000 | 0.4831          | 0.4882 |
| 0.4523        | 6.0   | 1500 | 0.4175          | 0.4201 |
| 0.3638        | 8.0   | 2000 | 0.4043          | 0.3913 |
| 0.3086        | 10.0  | 2500 | 0.4165          | 0.3847 |
| 0.2744        | 12.0  | 3000 | 0.4035          | 0.3639 |
| 0.2464        | 14.0  | 3500 | 0.4226          | 0.3595 |
| 0.2182        | 16.0  | 4000 | 0.4392          | 0.3485 |
| 0.197         | 18.0  | 4500 | 0.4512          | 0.3482 |
| 0.1803        | 20.0  | 5000 | 0.4476          | 0.3368 |
| 0.1626        | 22.0  | 5500 | 0.4684          | 0.3392 |
| 0.1522        | 24.0  | 6000 | 0.4792          | 0.3328 |
| 0.1418        | 26.0  | 6500 | 0.4716          | 0.3241 |
| 0.1317        | 28.0  | 7000 | 0.4988          | 0.3252 |
| 0.127         | 30.0  | 7500 | 0.4977          | 0.3249 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
