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: 0.6582
- Accuracy: 0.8824
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: 488
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.198 | 0.1270 | 62 | 1.4080 | 0.5532 |
| 0.8081 | 1.1270 | 124 | 1.5203 | 0.6596 |
| 0.3909 | 2.1270 | 186 | 1.2482 | 0.7021 |
| 0.2733 | 3.1270 | 248 | 1.1558 | 0.7447 |
| 0.0197 | 4.1270 | 310 | 0.9275 | 0.7660 |
| 0.0911 | 5.1270 | 372 | 1.1365 | 0.7660 |
| 0.0514 | 6.1270 | 434 | 0.7995 | 0.7872 |
| 0.0023 | 7.1107 | 488 | 0.7915 | 0.7872 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for rpham/videomae-base-finetuned-ucf101-subset
Base model
MCG-NJU/videomae-base