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anirudhmu
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videomae-base-finetuned-soccer-action-recognitionx4

Video Classification
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Safetensors
videomae
Generated from Trainer
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videomae-base-finetuned-soccer-action-recognitionx4 / README.md
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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-recognitionx4
    results: []

videomae-base-finetuned-soccer-action-recognitionx4

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: 0.1327
  • Accuracy: 0.9648

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: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 1125

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.02 28 1.3255 0.3782
No log 1.02 56 0.9903 0.5751
1.1078 2.02 84 0.4648 0.8238
1.1078 3.03 113 0.4075 0.8342
1.1078 4.02 141 0.2301 0.9275
0.2591 5.02 169 0.4090 0.8549
0.2591 6.02 197 0.1527 0.9482
0.2591 7.03 226 0.1413 0.9585
0.111 8.02 254 0.1386 0.9637
0.111 9.02 282 0.1674 0.9430
0.111 10.02 310 0.1010 0.9741
0.0509 11.03 339 0.1586 0.9637
0.0509 12.02 367 0.2696 0.8860
0.0509 13.02 395 0.3005 0.9171
0.023 14.02 423 0.1001 0.9741
0.023 15.03 452 0.1961 0.9482
0.0354 16.02 480 0.2596 0.9223
0.0354 17.02 508 0.1006 0.9689
0.0354 18.02 536 0.0947 0.9793
0.0141 19.03 565 0.0831 0.9793
0.0141 20.02 593 0.0685 0.9793
0.0141 21.02 621 0.0978 0.9689
0.0168 22.02 649 0.0812 0.9793
0.0168 23.03 678 0.0782 0.9793
0.0168 24.02 706 0.2624 0.9275
0.0029 25.02 734 0.1806 0.9534
0.0029 26.02 762 0.2123 0.9585
0.0029 27.03 791 0.2010 0.9482
0.0048 28.02 819 0.1259 0.9689
0.0048 29.02 847 0.2145 0.9430
0.0048 30.02 875 0.2901 0.9223
0.0042 31.03 904 0.0911 0.9793
0.0042 32.02 932 0.0892 0.9741
0.0024 33.02 960 0.0911 0.9845
0.0024 34.02 988 0.0987 0.9741
0.0024 35.03 1017 0.1446 0.9482
0.0008 36.02 1045 0.1415 0.9482
0.0008 37.02 1073 0.1435 0.9482
0.0008 38.02 1101 0.1438 0.9482
0.0008 39.02 1125 0.1371 0.9534

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.7
  • Tokenizers 0.15.0