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---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: videomae-base-finetuned-ucf-crimevbinaryv4
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-crimevbinaryv4
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: 0.8055
- Accuracy: 0.8571
- Precision: 0.8571
- Recall: 0.8571
- Auc: 0.9328
## 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: 8
- eval_batch_size: 8
- 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_steps: 500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4783 | 1.0 | 175 | 0.5235 | 0.78 | 0.7825 | 0.78 | 0.8269 |
| 0.6121 | 2.0 | 350 | 0.5076 | 0.816 | 0.8179 | 0.816 | 0.8518 |
| 0.3305 | 3.0 | 525 | 0.3910 | 0.856 | 0.8660 | 0.856 | 0.9222 |
| 0.2431 | 4.0 | 700 | 0.8684 | 0.728 | 0.8190 | 0.728 | 0.8933 |
| 0.3337 | 5.0 | 875 | 0.5653 | 0.808 | 0.8266 | 0.808 | 0.9149 |
| 0.1768 | 6.0 | 1050 | 0.4709 | 0.88 | 0.8803 | 0.88 | 0.9311 |
| 0.111 | 7.0 | 1225 | 0.6650 | 0.848 | 0.8600 | 0.848 | 0.9263 |
| 0.1507 | 8.0 | 1400 | 0.6151 | 0.852 | 0.8522 | 0.852 | 0.9232 |
| 0.1771 | 9.0 | 1575 | 0.6924 | 0.872 | 0.8729 | 0.872 | 0.9280 |
| 0.13 | 10.0 | 1750 | 0.6670 | 0.884 | 0.8846 | 0.884 | 0.9304 |
| 0.0062 | 11.0 | 1925 | 0.8110 | 0.86 | 0.8621 | 0.86 | 0.9198 |
| 0.0008 | 12.0 | 2100 | 0.8139 | 0.876 | 0.8768 | 0.876 | 0.9235 |
| 0.0004 | 13.0 | 2275 | 0.8727 | 0.868 | 0.8711 | 0.868 | 0.9258 |
| 0.0005 | 14.0 | 2450 | 1.0055 | 0.86 | 0.8658 | 0.86 | 0.9250 |
| 0.0002 | 15.0 | 2625 | 0.9728 | 0.864 | 0.8677 | 0.864 | 0.9269 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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