---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: violence-audio-Recognition-8
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8933333333333333
---

<!-- 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. -->

# violence-audio-Recognition-8

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: 0.2992
- Accuracy: 0.8933

## 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: 16
- 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_ratio: 0.01
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6436        | 1.0   | 19   | 0.5131          | 0.88     |
| 0.4122        | 2.0   | 38   | 0.3025          | 0.92     |
| 0.2646        | 3.0   | 57   | 0.3837          | 0.8533   |
| 0.1849        | 4.0   | 76   | 0.2705          | 0.9067   |
| 0.1755        | 5.0   | 95   | 0.1893          | 0.9467   |
| 0.1451        | 6.0   | 114  | 0.2229          | 0.92     |
| 0.1101        | 7.0   | 133  | 0.2182          | 0.9333   |
| 0.0948        | 8.0   | 152  | 0.2992          | 0.8933   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2