metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: violence-audio-Recognition-6
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: 0.8533333333333334
violence-audio-Recognition-6
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3720
- Accuracy: 0.8533
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6578 | 1.0 | 19 | 0.6249 | 0.68 |
| 0.5522 | 2.0 | 38 | 0.5115 | 0.76 |
| 0.4185 | 3.0 | 57 | 0.6679 | 0.72 |
| 0.3984 | 4.0 | 76 | 0.4802 | 0.8267 |
| 0.3332 | 5.0 | 95 | 0.3958 | 0.8533 |
| 0.2946 | 6.0 | 114 | 0.3720 | 0.8533 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2