Anomaly-Detection-D1
Collection
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Updated
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: 1.1903
- Accuracy: 0.7335
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1920
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5817 | 0.1255 | 241 | 0.6961 | 0.6601 |
| 0.4524 | 1.1255 | 482 | 1.1878 | 0.6009 |
| 0.5473 | 2.1255 | 723 | 1.0509 | 0.6420 |
| 0.5044 | 3.1255 | 964 | 1.0045 | 0.6745 |
| 0.7258 | 4.1255 | 1205 | 0.9840 | 0.6567 |
| 0.3606 | 5.1255 | 1446 | 1.0898 | 0.7377 |
| 0.2423 | 6.1255 | 1687 | 1.0520 | 0.7460 |
| 0.3488 | 7.1214 | 1920 | 1.1903 | 0.7335 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for skywalker290/videomae-videomae-d1
Base model
MCG-NJU/videomae-base