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metadata
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-base-finetuned-soccer-action-recognition
    results: []

videomae-base-finetuned-soccer-action-recognition

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

  • Loss: 0.2554
  • Accuracy: 0.9470

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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: 2728

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7115 0.03 85 1.4196 0.4
1.0097 1.03 170 0.7807 0.6759
0.6192 2.03 255 0.7952 0.7034
0.4713 3.03 341 0.6536 0.7931
0.3973 4.03 426 0.3638 0.8690
0.3633 5.03 511 0.3616 0.8966
0.2336 6.03 596 0.4579 0.8966
0.1997 7.03 682 1.5970 0.6069
0.2738 8.03 767 0.4102 0.8690
0.2492 9.03 852 0.7651 0.8345
0.1568 10.03 937 0.8561 0.8138
0.1856 11.03 1023 0.2811 0.9241
0.1296 12.03 1108 0.3444 0.9172
0.0782 13.03 1193 0.3423 0.9241
0.14 14.03 1278 0.3122 0.9241
0.0689 15.03 1364 0.3534 0.9172
0.036 16.03 1449 0.4815 0.9103
0.0695 17.03 1534 0.5698 0.8828
0.0618 18.03 1619 0.3053 0.9310
0.0553 19.03 1705 0.3443 0.9241
0.0301 20.03 1790 0.1427 0.9586
0.0412 21.03 1875 0.5619 0.8690
0.0492 22.03 1960 0.5701 0.8897
0.0171 23.03 2046 0.6377 0.8690
0.0181 24.03 2131 0.5981 0.8828
0.0305 25.03 2216 0.3178 0.9448
0.0393 26.03 2301 0.5434 0.9103
0.0248 27.03 2387 0.4097 0.9241
0.0146 28.03 2472 0.4427 0.9103
0.012 29.03 2557 0.5619 0.9034
0.0065 30.03 2642 0.5384 0.9103
0.009 31.03 2728 0.5014 0.9172

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1