---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: violence-audio-Recognition-1277
  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: 0.9622950819672131
---

<!-- 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-1277

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: 0.1281
- Accuracy: 0.9623

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.506         | 0.99  | 38   | 0.4232          | 0.8131   |
| 0.3105        | 1.99  | 76   | 0.2425          | 0.9230   |
| 0.2331        | 2.98  | 114  | 0.2139          | 0.9443   |
| 0.152         | 4.0   | 153  | 0.1698          | 0.9475   |
| 0.1517        | 4.99  | 191  | 0.1847          | 0.9508   |
| 0.1167        | 5.99  | 229  | 0.1134          | 0.9689   |
| 0.0933        | 6.98  | 267  | 0.1233          | 0.9672   |
| 0.0845        | 7.95  | 304  | 0.1281          | 0.9623   |


### Framework versions

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