---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: vivos
      type: vivos
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.0013157894736842105
---

<!-- 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"/>]()
# wav2vec2-base-finetuned-ks

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: 5.3540
- Accuracy: 0.0013

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7037        | 0.9997 | 1457 | 5.3540          | 0.0013   |
| 0.0203        | 2.0    | 2915 | 8.2572          | 0.0013   |
| 0.0718        | 2.9997 | 4372 | 9.1738          | 0.0      |
| 0.0027        | 4.0    | 5830 | 10.0341         | 0.0      |
| 0.0019        | 4.9983 | 7285 | 10.3670         | 0.0      |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.19.1