2nzi/videomae-surf-analytics-v2

videomae-surf-analytics-sans-wandb

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: 0.5544
• Accuracy: 0.8852
• F1: 0.8840

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: 1850

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
1.3096	0.2005	371	1.3267	0.4590	0.2888
1.0586	1.2005	742	1.2866	0.5820	0.5035
0.9781	2.2005	1113	0.7952	0.7459	0.7466
0.0034	3.2005	1484	0.7218	0.8361	0.8343
0.1895	4.1978	1850	0.5544	0.8852	0.8840

Framework versions

• Transformers 4.41.2
• Pytorch 2.1.0+cu118
• Datasets 2.19.2
• Tokenizers 0.19.1