videomae-base-finetuned-ucf-crimevbinaryv4

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: 0.8055
  • Accuracy: 0.8571
  • Precision: 0.8571
  • Recall: 0.8571
  • Auc: 0.9328

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
0.4783 1.0 175 0.5235 0.78 0.7825 0.78 0.8269
0.6121 2.0 350 0.5076 0.816 0.8179 0.816 0.8518
0.3305 3.0 525 0.3910 0.856 0.8660 0.856 0.9222
0.2431 4.0 700 0.8684 0.728 0.8190 0.728 0.8933
0.3337 5.0 875 0.5653 0.808 0.8266 0.808 0.9149
0.1768 6.0 1050 0.4709 0.88 0.8803 0.88 0.9311
0.111 7.0 1225 0.6650 0.848 0.8600 0.848 0.9263
0.1507 8.0 1400 0.6151 0.852 0.8522 0.852 0.9232
0.1771 9.0 1575 0.6924 0.872 0.8729 0.872 0.9280
0.13 10.0 1750 0.6670 0.884 0.8846 0.884 0.9304
0.0062 11.0 1925 0.8110 0.86 0.8621 0.86 0.9198
0.0008 12.0 2100 0.8139 0.876 0.8768 0.876 0.9235
0.0004 13.0 2275 0.8727 0.868 0.8711 0.868 0.9258
0.0005 14.0 2450 1.0055 0.86 0.8658 0.86 0.9250
0.0002 15.0 2625 0.9728 0.864 0.8677 0.864 0.9269

Framework versions

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