jialicheng / ucf101_videomae-large

huggingface.co
Total runs: 6
24-hour runs: 0
7-day runs: 1
30-day runs: -2
Model's Last Updated: August 27 2025
video-classification

Introduction of ucf101_videomae-large

Model Details of ucf101_videomae-large

ucf101_42

This model is a fine-tuned version of MCG-NJU/videomae-large on the ucf101 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3185
  • Accuracy: 0.9345
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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 298 0.5806 0.8423
No log 2.0 596 0.5192 0.8653
No log 3.0 894 0.4903 0.8814
0.5923 4.0 1192 0.4623 0.8901
0.5923 5.0 1490 0.3949 0.9005
0.5923 6.0 1788 0.4748 0.8844
0.0581 7.0 2086 0.4877 0.8820
0.0581 8.0 2385 0.3976 0.9131
0.0581 9.0 2683 0.3824 0.9116
0.0581 10.0 2981 0.3553 0.9171
0.0221 11.0 3279 0.3557 0.9229
0.0221 12.0 3577 0.3619 0.9258
0.0221 13.0 3875 0.3941 0.9214
0.0112 14.0 4173 0.3989 0.9145
0.0112 15.0 4471 0.3635 0.9236
0.0112 16.0 4770 0.3418 0.9285
0.005 17.0 5068 0.3374 0.9261
0.005 18.0 5366 0.3340 0.9333
0.005 19.0 5664 0.3294 0.9338
0.005 19.99 5960 0.3185 0.9345
Framework versions
  • Transformers 4.39.3
  • Pytorch 2.2.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2

Runs of jialicheng ucf101_videomae-large on huggingface.co

6
Total runs
0
24-hour runs
0
3-day runs
1
7-day runs
-2
30-day runs

More Information About ucf101_videomae-large huggingface.co Model

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ucf101_videomae-large install

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