---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-kinetics400-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. -->

# vivit-b-16x2-kinetics400-UCF-Crime

This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on UCF-Crime dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9757
- Accuracy: 0.6149

## 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: 8
- eval_batch_size: 8
- 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: 3132

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2072        | 0.06  | 196  | 1.6400          | 0.5518   |
| 1.5513        | 1.06  | 392  | 1.4988          | 0.5634   |
| 1.1038        | 2.06  | 588  | 1.5328          | 0.5861   |
| 0.9462        | 3.06  | 784  | 1.3932          | 0.6178   |
| 0.7387        | 4.06  | 980  | 1.5449          | 0.6060   |
| 0.5085        | 5.06  | 1176 | 1.3075          | 0.6287   |
| 0.4443        | 6.06  | 1372 | 1.6743          | 0.6001   |
| 0.4695        | 7.06  | 1568 | 1.5287          | 0.6172   |
| 0.4409        | 8.06  | 1764 | 1.7749          | 0.6089   |
| 0.1158        | 9.06  | 1960 | 1.9027          | 0.6076   |
| 0.1183        | 10.06 | 2156 | 1.9622          | 0.6085   |
| 0.1322        | 11.06 | 2352 | 2.0872          | 0.6152   |
| 0.1881        | 12.06 | 2548 | 2.0095          | 0.6094   |
| 0.0932        | 13.06 | 2744 | 1.9398          | 0.6232   |
| 0.0303        | 14.06 | 2940 | 1.9994          | 0.6134   |
| 0.0513        | 15.06 | 3132 | 1.9757          | 0.6149   |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.10.0+cu113
- Datasets 2.14.5
- Tokenizers 0.13.3