---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
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