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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: MCG-NJU/videomae-base
model-index:
- name: videomae-base-finetuned-ucf_crime2
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_crime2
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: 1.8463
- Accuracy: 0.5200
## 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: 2700
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.475 | 0.05 | 135 | 0.9935 | 0.6004 |
| 1.44 | 1.05 | 270 | 1.4196 | 0.4274 |
| 1.1084 | 2.05 | 405 | 0.9135 | 0.6737 |
| 0.8732 | 3.05 | 540 | 1.1984 | 0.5479 |
| 1.4184 | 4.05 | 675 | 1.3373 | 0.4926 |
| 1.1355 | 5.05 | 810 | 0.9888 | 0.6148 |
| 0.4522 | 6.05 | 945 | 1.0745 | 0.5694 |
| 0.7754 | 7.05 | 1080 | 1.5848 | 0.5330 |
| 1.1235 | 8.05 | 1215 | 1.3688 | 0.5753 |
| 1.611 | 9.05 | 1350 | 0.6958 | 0.7694 |
| 0.5714 | 10.05 | 1485 | 0.8027 | 0.7542 |
| 0.716 | 11.05 | 1620 | 1.3503 | 0.6782 |
| 0.6642 | 12.05 | 1755 | 1.0798 | 0.6957 |
| 0.8451 | 13.05 | 1890 | 1.2328 | 0.7479 |
| 0.6157 | 14.05 | 2025 | 1.9403 | 0.5762 |
| 0.3358 | 15.05 | 2160 | 1.3435 | 0.6939 |
| 0.5394 | 16.05 | 2295 | 1.2524 | 0.7056 |
| 0.3334 | 17.05 | 2430 | 1.1190 | 0.7645 |
| 0.3513 | 18.05 | 2565 | 1.2137 | 0.7461 |
| 0.2531 | 19.05 | 2700 | 1.2131 | 0.7362 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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