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videomae-base-finetuned-kinetics-finetuned-freeway-subset

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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-base-finetuned-kinetics-finetuned-freeway-subset
    results: []

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videomae-base-finetuned-kinetics-finetuned-freeway-subset

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: 0.0016
  • Accuracy: 1.0

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: 5
  • eval_batch_size: 5
  • 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: 1800

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6551 0.02 36 0.7171 0.5
0.6085 1.02 72 0.7057 0.5
0.5876 2.02 108 0.5834 0.75
0.5757 3.02 144 0.5360 0.7143
0.7017 4.02 180 0.4589 0.7143
0.5681 5.02 216 0.3667 0.8214
0.3418 6.02 252 0.2312 0.9286
0.6408 7.02 288 0.2724 0.8929
0.3846 8.02 324 0.1288 0.9643
0.1551 9.02 360 0.6198 0.8214
0.4879 10.02 396 0.3241 0.8571
0.0982 11.02 432 0.1815 0.9286
0.112 12.02 468 0.2504 0.9643
0.3627 13.02 504 0.2357 0.9643
0.2329 14.02 540 0.6101 0.8571
0.141 15.02 576 0.0218 1.0
0.1755 16.02 612 0.0791 0.9643
0.079 17.02 648 0.1167 0.9643
0.0859 18.02 684 0.0118 1.0
0.0131 19.02 720 0.0020 1.0
0.0014 20.02 756 0.0054 1.0
0.0008 21.02 792 0.0841 0.9286
0.0024 22.02 828 0.0852 0.9643
0.1803 23.02 864 0.0005 1.0
0.0001 24.02 900 0.0379 0.9643
0.0012 25.02 936 0.0705 0.9643
0.0018 26.02 972 0.0010 1.0
0.0007 27.02 1008 0.0210 1.0
0.0028 28.02 1044 0.0030 1.0
0.0465 29.02 1080 0.0005 1.0
0.0004 30.02 1116 0.0011 1.0
0.0016 31.02 1152 0.0005 1.0
0.0 32.02 1188 0.0012 1.0
0.0002 33.02 1224 0.0001 1.0
0.0315 34.02 1260 0.0027 1.0
0.0253 35.02 1296 0.0003 1.0
0.0011 36.02 1332 0.0022 1.0
0.0001 37.02 1368 0.0006 1.0
0.0007 38.02 1404 0.0120 1.0
0.0001 39.02 1440 0.1001 0.9643
0.0005 40.02 1476 0.0331 0.9643
0.0009 41.02 1512 0.0418 0.9643
0.0035 42.02 1548 0.0761 0.9643
0.0001 43.02 1584 0.0020 1.0
0.0001 44.02 1620 0.0020 1.0
0.0 45.02 1656 0.0010 1.0
0.0001 46.02 1692 0.0009 1.0
0.0005 47.02 1728 0.0012 1.0
0.0001 48.02 1764 0.0015 1.0
0.0002 49.02 1800 0.0016 1.0

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.1.1
  • Datasets 2.19.2
  • Tokenizers 0.19.1