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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-vios-v1
  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-v1

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: 0.6352
- Wer: 0.5161

## 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: 16
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.7944        | 3.98  | 1000  | 1.7427          | 1.0387 |
| 0.7833        | 7.97  | 2000  | 0.4026          | 0.4364 |
| 0.4352        | 11.95 | 3000  | 0.3967          | 0.4042 |
| 0.4988        | 15.94 | 4000  | 0.5446          | 0.4632 |
| 0.7822        | 19.92 | 5000  | 0.6563          | 0.5491 |
| 0.8496        | 23.9  | 6000  | 0.5828          | 0.5045 |
| 0.8072        | 27.89 | 7000  | 0.6318          | 0.5109 |
| 0.8336        | 31.87 | 8000  | 0.6352          | 0.5161 |
| 0.8311        | 35.86 | 9000  | 0.6352          | 0.5161 |
| 0.839         | 39.84 | 10000 | 0.6352          | 0.5161 |
| 0.8297        | 43.82 | 11000 | 0.6352          | 0.5161 |
| 0.8288        | 47.81 | 12000 | 0.6352          | 0.5161 |


### Framework versions

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