videomae-base-finetuned-ucf101-subset
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: 0.3235
- Accuracy: 0.9355
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: 4
- eval_batch_size: 4
- 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: 1875
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.198 | 0.04 | 75 | 2.0868 | 0.4 |
1.3004 | 1.04 | 150 | 1.0574 | 0.6714 |
0.6807 | 2.04 | 225 | 0.5173 | 0.8 |
0.8481 | 3.04 | 300 | 0.9220 | 0.7 |
0.2129 | 4.04 | 375 | 0.4430 | 0.7857 |
0.3205 | 5.04 | 450 | 0.4711 | 0.8571 |
0.1059 | 6.04 | 525 | 0.0504 | 0.9857 |
0.0048 | 7.04 | 600 | 0.6079 | 0.8857 |
0.043 | 8.04 | 675 | 0.5023 | 0.8714 |
0.0061 | 9.04 | 750 | 0.5091 | 0.8571 |
0.0029 | 10.04 | 825 | 0.0924 | 0.9571 |
0.0022 | 11.04 | 900 | 0.0082 | 1.0 |
0.1303 | 12.04 | 975 | 0.2828 | 0.9429 |
0.0054 | 13.04 | 1050 | 0.1975 | 0.9429 |
0.0019 | 14.04 | 1125 | 0.1887 | 0.9429 |
0.0015 | 15.04 | 1200 | 0.7790 | 0.8571 |
0.0017 | 16.04 | 1275 | 0.2677 | 0.9286 |
0.0014 | 17.04 | 1350 | 0.3186 | 0.9286 |
0.0012 | 18.04 | 1425 | 0.2961 | 0.9429 |
0.0012 | 19.04 | 1500 | 0.4832 | 0.9 |
0.0011 | 20.04 | 1575 | 0.3789 | 0.9429 |
0.001 | 21.04 | 1650 | 0.2051 | 0.9571 |
0.0011 | 22.04 | 1725 | 0.1955 | 0.9714 |
0.0011 | 23.04 | 1800 | 0.1916 | 0.9714 |
0.0013 | 24.04 | 1875 | 0.1907 | 0.9714 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model state unknown