--- license: apache-2.0 base_model: facebook/wav2vec2-base-960h tags: - generated_from_trainer datasets: - audiofolder metrics: - accuracy model-index: - name: violence-detect-44 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 --- # violence-detect-44 This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 0.3533 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6788 | 1.0 | 19 | 0.6183 | 0.6 | | 0.6395 | 2.0 | 38 | 0.5397 | 0.8533 | | 0.5565 | 3.0 | 57 | 0.4855 | 0.8667 | | 0.5235 | 4.0 | 76 | 0.3962 | 0.9067 | | 0.4561 | 5.0 | 95 | 0.3675 | 0.8933 | | 0.4113 | 6.0 | 114 | 0.3872 | 0.8667 | | 0.5303 | 7.0 | 133 | 0.3533 | 0.8933 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2