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: 0.2708
- Accuracy: 0.9032
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: 8
- eval_batch_size: 8
- 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: 300
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7999 | 0.13 | 38 | 0.7968 | 0.7143 |
0.3574 | 1.13 | 76 | 0.6632 | 0.7571 |
0.1651 | 2.13 | 114 | 0.3926 | 0.8429 |
0.0843 | 3.13 | 152 | 0.3751 | 0.8714 |
0.1116 | 4.13 | 190 | 0.3232 | 0.9286 |
0.0123 | 5.13 | 228 | 0.1498 | 0.9429 |
0.0188 | 6.13 | 266 | 0.4283 | 0.9 |
0.0146 | 7.11 | 300 | 0.4197 | 0.9 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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