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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf_crime
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# videomae-base-finetuned-ucf_crime
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0871
- Accuracy: 0.5058
## 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: 2
- eval_batch_size: 2
- 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: 6000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6487 | 0.02 | 120 | 0.6813 | 0.6989 |
| 0.4529 | 1.02 | 240 | 0.7467 | 0.5678 |
| 0.5165 | 2.02 | 360 | 0.7600 | 0.7264 |
| 0.9203 | 3.02 | 480 | 0.6189 | 0.6517 |
| 1.2667 | 4.02 | 600 | 0.6702 | 0.6511 |
| 1.0452 | 5.02 | 720 | 0.5703 | 0.7592 |
| 0.3893 | 6.02 | 840 | 0.5524 | 0.7397 |
| 1.2013 | 7.02 | 960 | 0.7470 | 0.6109 |
| 1.4903 | 8.02 | 1080 | 1.0094 | 0.5695 |
| 0.5434 | 9.02 | 1200 | 0.5189 | 0.7586 |
| 0.8344 | 10.02 | 1320 | 0.7674 | 0.5552 |
| 1.1621 | 11.02 | 1440 | 0.9610 | 0.5874 |
| 0.8743 | 12.02 | 1560 | 0.8160 | 0.6448 |
| 0.7118 | 13.02 | 1680 | 0.6015 | 0.6592 |
| 0.8404 | 14.02 | 1800 | 0.7149 | 0.7661 |
| 1.0397 | 15.02 | 1920 | 0.6360 | 0.7770 |
| 1.3511 | 16.02 | 2040 | 0.9110 | 0.6523 |
| 1.0257 | 17.02 | 2160 | 1.0642 | 0.5891 |
| 1.0726 | 18.02 | 2280 | 0.7299 | 0.8213 |
| 0.5609 | 19.02 | 2400 | 0.8921 | 0.6408 |
| 0.495 | 20.02 | 2520 | 0.7762 | 0.7632 |
| 1.6306 | 21.02 | 2640 | 0.9976 | 0.7092 |
| 1.0072 | 22.02 | 2760 | 0.5697 | 0.8029 |
| 0.4503 | 23.02 | 2880 | 0.8448 | 0.6914 |
| 0.8306 | 24.02 | 3000 | 0.9617 | 0.7351 |
| 0.8824 | 25.02 | 3120 | 1.1839 | 0.6759 |
| 0.837 | 26.02 | 3240 | 1.6406 | 0.6075 |
| 0.4214 | 27.02 | 3360 | 1.1276 | 0.6920 |
| 0.5166 | 28.02 | 3480 | 1.0815 | 0.7626 |
| 0.6925 | 29.02 | 3600 | 1.1492 | 0.7086 |
| 0.2864 | 30.02 | 3720 | 1.1919 | 0.7345 |
| 0.463 | 31.02 | 3840 | 1.3524 | 0.6937 |
| 1.1162 | 32.02 | 3960 | 1.8301 | 0.5822 |
| 0.0033 | 33.02 | 4080 | 1.4447 | 0.6891 |
| 0.002 | 34.02 | 4200 | 1.6565 | 0.6960 |
| 0.0017 | 35.02 | 4320 | 1.5357 | 0.7282 |
| 0.2289 | 36.02 | 4440 | 1.9812 | 0.6397 |
| 0.4801 | 37.02 | 4560 | 2.2316 | 0.6167 |
| 1.0323 | 38.02 | 4680 | 2.1380 | 0.5822 |
| 0.0715 | 39.02 | 4800 | 1.9264 | 0.6345 |
| 0.0024 | 40.02 | 4920 | 2.6257 | 0.5023 |
| 0.4734 | 41.02 | 5040 | 1.8666 | 0.6316 |
| 0.3108 | 42.02 | 5160 | 1.5493 | 0.7299 |
| 0.2318 | 43.02 | 5280 | 2.0831 | 0.6333 |
| 0.6623 | 44.02 | 5400 | 2.3276 | 0.6029 |
| 0.0011 | 45.02 | 5520 | 2.0469 | 0.6684 |
| 0.32 | 46.02 | 5640 | 2.4646 | 0.6138 |
| 0.0054 | 47.02 | 5760 | 2.5998 | 0.5897 |
| 0.2733 | 48.02 | 5880 | 2.7594 | 0.5638 |
| 0.0005 | 49.02 | 6000 | 2.8625 | 0.55 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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