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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-crimevbinary-balanced-vwandb
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-crimevbinary-balanced-vwandb
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: 0.2106
- Accuracy: 0.9444
- Precision: 0.9444
- Recall: 0.9444
- Auc: 0.9815
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6542 | 1.0 | 29 | 0.6413 | 0.6389 | 0.7217 | 0.6389 | 0.8056 |
| 0.574 | 2.0 | 58 | 0.5412 | 0.75 | 0.7945 | 0.75 | 0.8827 |
| 0.4214 | 3.0 | 87 | 0.4414 | 0.8611 | 0.8714 | 0.8611 | 0.9228 |
| 0.4331 | 4.0 | 116 | 0.4604 | 0.8056 | 0.8311 | 0.8056 | 0.8889 |
| 0.2981 | 5.0 | 145 | 0.3923 | 0.8889 | 0.8937 | 0.8889 | 0.9321 |
| 0.2615 | 6.0 | 174 | 0.5136 | 0.8333 | 0.8506 | 0.8333 | 0.8735 |
| 0.1896 | 7.0 | 203 | 0.4989 | 0.8889 | 0.9091 | 0.8889 | 0.9105 |
| 0.5031 | 8.0 | 232 | 0.3814 | 0.9167 | 0.9180 | 0.9167 | 0.9321 |
| 0.0947 | 9.0 | 261 | 0.4635 | 0.8889 | 0.8937 | 0.8889 | 0.9290 |
| 0.3865 | 10.0 | 290 | 0.5199 | 0.8889 | 0.9091 | 0.8889 | 0.8951 |
| 0.187 | 11.0 | 319 | 0.6748 | 0.8611 | 0.8622 | 0.8611 | 0.9136 |
| 0.0408 | 12.0 | 348 | 1.0193 | 0.8056 | 0.8143 | 0.8056 | 0.9012 |
| 0.3851 | 13.0 | 377 | 0.3708 | 0.8889 | 0.8889 | 0.8889 | 0.9630 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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