metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: violence-audio-Recognition-666
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: 0.9645748987854251
violence-audio-Recognition-666
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: 0.1258
- Accuracy: 0.9646
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 |
|---|---|---|---|---|
| 0.4755 | 0.99 | 61 | 0.3227 | 0.8715 |
| 0.2665 | 1.99 | 123 | 0.2088 | 0.9322 |
| 0.1808 | 3.0 | 185 | 0.1783 | 0.9474 |
| 0.1505 | 4.0 | 247 | 0.1528 | 0.9504 |
| 0.1158 | 4.99 | 308 | 0.1260 | 0.9615 |
| 0.0928 | 5.99 | 370 | 0.1302 | 0.9656 |
| 0.0792 | 7.0 | 432 | 0.1327 | 0.9626 |
| 0.0707 | 7.9 | 488 | 0.1258 | 0.9646 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2