--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy - precision - recall model-index: - name: videomae-base-finetuned-ucf-crimevbinary-balancedv6 results: [] --- # videomae-base-finetuned-ucf-crimevbinary-balancedv6 This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6175 - Accuracy: 0.8475 - Precision: 0.8572 - Recall: 0.8475 - Auc: 0.9263 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Auc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.5676 | 1.0 | 165 | 0.5685 | 0.6608 | 0.6975 | 0.6608 | 0.8059 | | 0.5645 | 2.0 | 330 | 0.3607 | 0.8481 | 0.8509 | 0.8481 | 0.9362 | | 0.4638 | 3.0 | 495 | 0.5746 | 0.8021 | 0.8226 | 0.8021 | 0.8919 | | 0.5765 | 4.0 | 660 | 0.3634 | 0.8622 | 0.8626 | 0.8622 | 0.9262 | | 0.4146 | 5.0 | 825 | 0.5092 | 0.8092 | 0.8302 | 0.8092 | 0.9225 | | 0.4319 | 6.0 | 990 | 0.4897 | 0.8799 | 0.8811 | 0.8799 | 0.9316 | | 0.3396 | 7.0 | 1155 | 0.5233 | 0.8587 | 0.8599 | 0.8587 | 0.9257 | | 0.1152 | 8.0 | 1320 | 0.6568 | 0.8763 | 0.8767 | 0.8763 | 0.9190 | | 0.0578 | 9.0 | 1485 | 0.6344 | 0.8693 | 0.8716 | 0.8693 | 0.9321 | | 0.0029 | 10.0 | 1650 | 0.7321 | 0.8728 | 0.8739 | 0.8728 | 0.9280 | | 0.1363 | 11.0 | 1815 | 0.7399 | 0.8622 | 0.8636 | 0.8622 | 0.9215 | ### Framework versions - Transformers 4.47.0.dev0 - Pytorch 2.5.1+cu124 - Datasets 3.1.0 - Tokenizers 0.20.3