videomae-base-finetuned-kinetics-finetuned_aggression_small

This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0896
• Accuracy: 0.6492

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: 0.0001
• 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: 580

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4363	0.1017	59	1.3741	0.4748
0.8512	1.1017	118	1.4081	0.4496
0.6126	2.1017	177	1.4804	0.5144
0.5229	3.1017	236	1.3253	0.5072
0.5223	4.1017	295	1.3315	0.5432
0.2361	5.1017	354	1.5060	0.5504
0.1656	6.1017	413	1.5207	0.5683
0.1531	7.1017	472	1.5595	0.5504
0.1112	8.1017	531	1.6025	0.5432
0.0567	9.0845	580	1.6007	0.5647

Framework versions

• Transformers 4.48.1
• Pytorch 2.5.1+cu118
• Datasets 3.2.0
• Tokenizers 0.21.0