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metadata
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-crimevbinaryv5
    results: []

videomae-base-finetuned-ucf-crimevbinaryv5

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5233
  • Accuracy: 0.8730
  • Precision: 0.8739
  • Recall: 0.8730
  • Auc: 0.9382

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
0.5298 1.0 173 0.4598 0.7952 0.8100 0.7952 0.8607
0.3824 2.0 346 0.3941 0.8434 0.8456 0.8434 0.9138
0.4836 3.0 519 0.5244 0.8032 0.8348 0.8032 0.9153
0.5522 4.0 692 0.6005 0.7149 0.8064 0.7149 0.8669
0.3953 5.0 865 0.5102 0.8474 0.8512 0.8474 0.9071
0.4682 6.0 1038 0.5437 0.8715 0.8765 0.8715 0.9211
0.2755 7.0 1211 0.7215 0.8434 0.8668 0.8434 0.9279
0.0752 8.0 1384 0.8213 0.8554 0.8697 0.8554 0.9166
0.0448 9.0 1557 0.8370 0.8554 0.8571 0.8554 0.8999
0.0122 10.0 1730 0.7837 0.8715 0.8718 0.8715 0.9109
0.0294 11.0 1903 0.8141 0.8715 0.8718 0.8715 0.9079

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3