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metadata
license: cc-by-nc-4.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-base-short-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-k
    results: []

videomae-base-short-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-k

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

  • Loss: 1.0855
  • Accuracy: 0.6764

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

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3699 0.06 200 0.2920 0.8925
0.3127 1.06 400 0.6035 0.77
0.2864 2.06 600 0.5088 0.8237
0.1739 3.06 800 0.6310 0.765
0.1835 4.06 1000 0.3643 0.8738
0.1075 5.06 1200 0.3455 0.8862
0.1362 6.06 1400 0.9145 0.75
0.2958 7.06 1600 0.3544 0.895
0.1571 8.06 1800 0.3748 0.8912
0.2448 9.06 2000 0.3646 0.8975
0.1939 10.06 2200 0.4430 0.8762
0.0666 11.06 2400 0.4916 0.8762
0.1958 12.06 2600 0.5114 0.8638
0.1063 13.06 2800 0.5701 0.8612
0.1047 14.06 3000 0.5226 0.8688
0.0131 15.06 3200 0.4656 0.8812

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.2