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: 0.1362
- Accuracy: 0.9714
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: 600
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2638 | 0.06 | 38 | 2.2761 | 0.1143 |
| 1.6112 | 1.06 | 76 | 1.0811 | 0.7143 |
| 0.5768 | 2.06 | 114 | 0.4538 | 0.8857 |
| 0.298 | 3.06 | 152 | 0.4841 | 0.8 |
| 0.0856 | 4.06 | 190 | 0.6021 | 0.8 |
| 0.2283 | 5.06 | 228 | 0.2103 | 0.9286 |
| 0.0559 | 6.06 | 266 | 0.1142 | 0.9714 |
| 0.2279 | 7.06 | 304 | 0.1132 | 0.9714 |
| 0.0145 | 8.06 | 342 | 0.0762 | 0.9714 |
| 0.0057 | 9.06 | 380 | 0.0226 | 1.0 |
| 0.0076 | 10.06 | 418 | 0.1619 | 0.9714 |
| 0.0046 | 11.06 | 456 | 0.1617 | 0.9714 |
| 0.0034 | 12.06 | 494 | 0.1676 | 0.9571 |
| 0.0034 | 13.06 | 532 | 0.1398 | 0.9714 |
| 0.0034 | 14.06 | 570 | 0.1345 | 0.9714 |
| 0.0035 | 15.05 | 600 | 0.1362 | 0.9714 |
Framework versions
- Transformers 4.33.2
- Pytorch 1.10.0+cu113
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
MCG-NJU/videomae-base