---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
- f1
model-index:
- name: wav2vec2-base-finetuned-ks
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: Data_Train
      split: train
      args: Data_Train
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8127696289905091
    - name: F1
      type: f1
      value: 0.7948883642136002
---

<!-- 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-finetuned-ks

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9323
- Accuracy: 0.8128
- F1: 0.7949

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.844         | 1.0   | 1449 | 1.7968          | 0.5065   | 0.3818 |
| 0.8796        | 2.0   | 2898 | 1.1875          | 0.6799   | 0.6273 |
| 0.7076        | 3.0   | 4347 | 1.0995          | 0.7584   | 0.7287 |
| 0.4669        | 4.0   | 5796 | 0.9960          | 0.7886   | 0.7675 |
| 0.2156        | 5.0   | 7245 | 0.9323          | 0.8128   | 0.7949 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3