Anomaly-Detection-D1
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Timesformer-Timesformer-d1
This model is a fine-tuned version of facebook/timesformer-base-finetuned-k400 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3666
- Accuracy: 0.7858
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: 1
- eval_batch_size: 1
- 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: 12010
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.175 | 0.1 | 1201 | 2.3533 | 0.6138 |
| 1.0596 | 1.1 | 2402 | 2.0203 | 0.6365 |
| 0.4307 | 2.1 | 3603 | 1.3942 | 0.7236 |
| 0.0014 | 3.1 | 4804 | 1.6228 | 0.7173 |
| 1.0661 | 4.1 | 6005 | 1.5961 | 0.6632 |
| 0.0005 | 5.1 | 7206 | 1.6165 | 0.7348 |
| 0.56 | 6.1 | 8407 | 1.5308 | 0.7403 |
| 1.1296 | 7.1 | 9608 | 1.4128 | 0.7527 |
| 0.8918 | 8.1 | 10809 | 1.4968 | 0.7841 |
| 0.6107 | 9.1 | 12010 | 1.3666 | 0.7858 |
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-timesformer-d1
Base model
facebook/timesformer-base-finetuned-k400