videomae-finetuned / README.md
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metadata
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-finetuned
    results: []

videomae-finetuned

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: 0.1289
  • Accuracy: 0.9706

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.2
  • training_steps: 8620

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7657 0.05 432 0.6104 0.8243
0.4011 1.05 864 0.4283 0.8896
0.301 2.05 1296 0.3957 0.8833
0.2967 3.05 1728 0.3066 0.9138
0.229 4.05 2160 0.3268 0.9092
0.2185 5.05 2592 0.2865 0.9281
0.1863 6.05 3024 0.2550 0.9320
0.1386 7.05 3456 0.2366 0.9422
0.1542 8.05 3888 0.2162 0.9449
0.1396 9.05 4320 0.2069 0.9424
0.1323 10.05 4752 0.2021 0.9486
0.1008 11.05 5184 0.2408 0.9465
0.0756 12.05 5616 0.2023 0.9509
0.0628 13.05 6048 0.1730 0.9609
0.0747 14.05 6480 0.1747 0.9622
0.047 15.05 6912 0.1698 0.9629
0.0586 16.05 7344 0.1412 0.9668
0.0644 17.05 7776 0.1314 0.9704
0.0521 18.05 8208 0.1343 0.9688
0.0516 19.05 8620 0.1289 0.9706

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2