videomae-base-finetuned-dd

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

• Loss: 0.4577
• Accuracy: 0.8909

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: 2
• eval_batch_size: 2
• 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: 1352

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5777	0.2485	336	0.8214	0.8373
1.144	1.2493	673	0.4453	0.8754
0.2783	2.2493	1010	0.8930	0.8171
0.0037	3.2470	1344	0.4077	0.8979
0.2113	4.0059	1352	0.4079	0.8979

Framework versions

• Transformers 4.40.2
• Pytorch 1.12.0+cu113
• Datasets 2.19.1
• Tokenizers 0.19.1