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videomae-large-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-kl-torch2

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

  • Loss: 0.6146
  • Accuracy: 0.7212

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 3200
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.361 0.06 200 0.2425 0.895
0.3449 1.06 400 0.6639 0.68
0.2435 2.06 600 0.9180 0.6663
0.2001 3.06 800 0.5656 0.7662
0.1405 4.06 1000 0.3859 0.86
0.1845 5.06 1200 0.3825 0.8675
0.1586 6.06 1400 1.4446 0.6687
0.2013 7.06 1600 0.4730 0.8562
0.2113 8.06 1800 0.3328 0.8862
0.245 9.06 2000 0.3519 0.8938
0.1767 10.06 2200 0.4004 0.895
0.1688 11.06 2400 0.6468 0.86
0.2823 12.06 2600 0.6006 0.8575
0.0928 13.06 2800 0.5516 0.875
0.0079 14.06 3000 0.5855 0.87
0.0325 15.06 3200 0.4921 0.8925

Framework versions

  • Transformers 4.27.4
  • Pytorch 2.0.0+cu117
  • Datasets 2.11.0
  • Tokenizers 0.13.2
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