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 on the Acts of Agression (cttv footage fights) 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