videomae-sft

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: 0.4701
• Accuracy: 0.8129

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: 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: 148

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.1745	0.2568	38	1.9429	0.3571
1.2196	1.2568	76	0.9690	0.6857
0.5598	2.2568	114	0.5722	0.8143
0.3387	3.2297	148	0.4453	0.8429

Framework versions

• Transformers 4.45.1
• Pytorch 2.5.1
• Datasets 3.2.0
• Tokenizers 0.20.0