transformers tensorboard safetensors videomae video-classification generated_from_trainer dataset:Pinwheel/ActsOfAgression base_model:MCG-NJU/videomae-base license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-fight-nofight-subset2
  results: []
datasets:
- Pinwheel/ActsOfAgression
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# videomae-base-finetuned-fight-nofight-subset2

**NOTE: This is experimentational if youre expecting this to work accurately (it wont) or be useful should probably look eslewhere😛** 


This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on the [Acts of Agression (cttv footage fights)](https://huggingface.co/datasets/Pinwheel/ActsOfAgression) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5190
- Accuracy: 0.7435

## Model description

Classifies video input into "Fight" or "No Fight" Class


## Intended uses & limitations

Can be used to detect fights/crime in cctv footage


### 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: 252
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5145        | 0.25  | 64   | 0.7845          | 0.5075   |
| 0.607         | 1.25  | 128  | 0.6886          | 0.6343   |
| 0.3986        | 2.25  | 192  | 0.5106          | 0.7463   |
| 0.3632        | 3.24  | 252  | 0.7408          | 0.6716   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1