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---
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
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