videomae-base-finetuned-ucf101

This model is a fine-tuned version of MCG-NJU/videomae-base on UCF101 dataset. It achieves the following results on the evaluation set:

• Loss: 1.1001
• Accuracy: 0.8054

Model description

transformers.VideoMAEForVideoClassification

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: 19780

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0704	0.2	3956	1.7583	0.5346
0.1936	1.2	7912	1.0780	0.7189
0.1014	2.2	11868	1.1839	0.7416
0.0049	3.2	15824	1.0054	0.7901
0.0012	4.2	19780	0.9529	0.8205

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3