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: 0.8504
- Accuracy: 0.7059
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: 3e-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: 68
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4845 | 0.19 | 13 | 0.6341 | 0.5294 |
| 0.6466 | 1.19 | 26 | 0.9443 | 0.4706 |
| 0.3798 | 2.19 | 39 | 0.9459 | 0.6471 |
| 0.3392 | 3.19 | 52 | 1.1101 | 0.6471 |
| 0.191 | 4.19 | 65 | 0.8548 | 0.6471 |
| 0.191 | 5.04 | 68 | 0.8504 | 0.7059 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for avidorger/videomae-base-finetuned-ucf101-subset
Base model
MCG-NJU/videomae-base