---
library_name: transformers
license: mit
base_model: prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-kinetics400-UCF-Crime-finetuned-AbnormalVideosOnly
  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-finetuned-AbnormalVideosOnly

This model is a fine-tuned version of [prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime](https://huggingface.co/prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6304
- Accuracy: 0.0962

## 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: 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_ratio: 0.1
- training_steps: 202

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.5324        | 0.5050 | 102  | 2.6516          | 0.0739   |
| 2.4308        | 1.4950 | 202  | 2.6304          | 0.0962   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.1.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0