videomae-finetuned-nba-5-class-4-batch-8000-vid-multiclass-4

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: 0.7974
  • F1: 0.8701
  • Accuracy: 0.8701

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: 1.5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 50000

Training results

Training Loss Epoch Step Validation Loss F1 Accuracy
1.3802 0.04 2000 1.2381 0.52 0.52
1.0115 1.04 4000 1.0522 0.6684 0.6684
0.9749 2.04 6000 0.9298 0.7537 0.7537
0.9048 3.04 8000 0.8679 0.7863 0.7863
0.7977 4.04 10000 0.8846 0.7811 0.7811
0.9259 5.04 12000 0.8018 0.8263 0.8263
0.6077 6.04 14000 0.8212 0.8189 0.8189
0.7102 7.04 16000 0.7876 0.8242 0.8242
0.5726 8.04 18000 0.8805 0.8232 0.8232
0.7768 9.04 20000 0.7490 0.8589 0.8589
0.6793 10.04 22000 0.7730 0.8558 0.8558
0.5765 11.04 24000 0.7752 0.8368 0.8368
0.4789 12.04 26000 0.7902 0.8484 0.8484
0.7398 13.04 28000 0.7603 0.8568 0.8568
0.6807 14.04 30000 0.7531 0.8716 0.8716
0.3262 15.04 32000 0.7663 0.8768 0.8768
0.4387 16.04 34000 0.7549 0.88 0.88
0.5013 17.04 36000 0.7713 0.8737 0.8737
0.9572 18.04 38000 0.7613 0.8684 0.8684
1.0645 19.04 40000 0.7618 0.8811 0.8811
0.4949 20.04 42000 0.7882 0.8747 0.8747
0.6131 21.04 44000 0.7964 0.8705 0.8705
0.628 22.04 46000 0.8089 0.8747 0.8747
0.5693 23.04 48000 0.8010 0.8747 0.8747
0.4764 24.04 50000 0.8117 0.8789 0.8789

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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