videomae-base-finetuned-ucf101-subset-frequency
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: 0.5657
- Accuracy: 0.7726
Model description
More information needed
Intended uses & limitations
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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: 1480
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.8818 | 0.1 | 148 | 0.5919 | 0.7111 |
0.6337 | 1.1 | 296 | 0.5929 | 0.7111 |
0.6245 | 2.1 | 444 | 0.7150 | 0.6085 |
0.6549 | 3.1 | 592 | 0.6096 | 0.7556 |
0.658 | 4.1 | 740 | 0.7169 | 0.6735 |
0.6981 | 5.1 | 888 | 0.6050 | 0.7726 |
0.619 | 6.1 | 1036 | 0.5278 | 0.7709 |
0.6163 | 7.1 | 1184 | 0.5167 | 0.7778 |
0.3778 | 8.1 | 1332 | 0.5298 | 0.7812 |
0.5459 | 9.1 | 1480 | 0.5657 | 0.7726 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
MCG-NJU/videomae-base