videomae-base-finetuned-kinetics-final-contest

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

  • Loss: 0.6795
  • Accuracy: 0.8458

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: 9e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 2464

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0054 0.0913 225 0.9635 0.7764
0.3981 1.0913 450 0.7286 0.7747
0.1595 2.0913 675 0.6008 0.8215
0.0302 3.0913 900 0.7152 0.8024
0.015 4.0913 1125 0.7613 0.7903
0.0019 5.0913 1350 0.6450 0.8354
0.0037 6.0913 1575 0.5948 0.8510
0.0037 7.0913 1800 0.6545 0.8354
0.0005 8.0913 2025 0.6526 0.8440
0.0005 9.0913 2250 0.6803 0.8458
0.0004 10.0869 2464 0.6795 0.8458

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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