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

作者 omermazig · 下载 93 · 点赞 0 · 更新 2023-11-04

generated_from_trainer

videomae-finetuned-nba-5-class-8-batch-8000-vid-multiclass

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:

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:

Training results

Training Loss Epoch Step Accuracy F1 Validation Loss
1.201 0.1 1000 0.5063 0.5063 1.2871
0.7867 1.1 2000 0.6105 0.6105 1.1560
0.8387 0.1 3000 0.6695 0.6695 1.0269
0.7537 1.1 4000 0.7295 0.7295 0.9678
0.6444 2.1 5000 0.6853 0.6853 1.0220
0.7003 3.1 6000 0.7347 0.7347 0.9334
0.753 0.1 7000 0.7432 0.7432 0.9021
0.5269 1.1 8000 0.7789 0.7789 0.8279
0.6577 2.1 9000 0.7989 0.7989 0.7635
0.6222 3.1 10000 0.8126 0.8126 0.8054
0.8643 0.05 11000 0.7537 0.7537 0.9539
0.714 0.05 12000 0.7747 0.7747 0.8765
0.5181 1.05 13000 0.7726 0.7726 0.8558
0.4201 0.05 14000 0.8011 0.8011 0.8045
0.5374 1.05 15000 0.7884 0.7884 0.8136
0.4644 2.05 16000 0.7821 0.7821 0.8639
0.6452 3.05 17000 0.8179 0.8179 0.8085
0.4075 0.05 18000 0.7916 0.7916 0.8793
0.3501 1.05 19000 0.8221 0.8221 0.8139
0.4375 2.05 20000 0.8147 0.8147 0.8130
0.6524 0.03 21000 0.7537 0.7537 0.9271
0.5446 0.03 22000 0.78 0.78 0.8799
0.4624 0.03 23000 0.7884 0.7884 0.9210
0.466 1.02 24000 0.7842 0.7842 0.8601
0.6521 0.03 25000 0.7684 0.7684 0.9876
0.4043 0.03 26000 0.7789 0.7789 0.9454
0.5166 0.03 28000 0.7411 0.7411 1.1252
0.5039 1.03 30000 0.7537 0.7537 1.1474
0.6505 2.03 32000 0.7358 0.7358 1.0888
0.7491 3.03 34000 0.7747 0.7747 1.0014
0.8005 4.03 36000 0.7642 0.7642 1.0938
0.4648 0.03 38000 1.0662 0.7789 0.7789
0.2227 1.03 40000 1.2853 0.7537 0.7537
1.0841 2.03 42000 1.2443 0.7653 0.7653
0.514 3.03 44000 1.2017 0.78 0.78
0.4064 4.03 46000 1.3686 0.7547 0.7547
0.4566 5.03 48000 1.2185 0.7821 0.7821
0.9526 6.03 50000 1.2917 0.7947 0.7947
0.8275 7.03 52000 1.2091 0.8063 0.8063
0.3083 8.03 54000 1.2351 0.8021 0.8021
0.1902 9.03 56000 1.3653 0.7937 0.7937
0.2955 10.03 58000 1.3334 0.7958 0.7958
0.3169 11.03 60000 1.2957 0.8126 0.8126

Framework versions