vit_wlasl_100__signer_20ep_coR

This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.2249
• Accuracy: 0.6893

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
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• 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: 3600
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
18.6766	0.05	180	4.5404	0.0444
16.8426	1.0499	360	3.8874	0.1598
12.3673	2.0499	540	2.9966	0.3432
7.8621	3.0501	721	2.4038	0.4852
4.8313	4.05	901	2.0418	0.5592
2.7708	5.0499	1081	1.8076	0.5740
1.5035	6.0499	1261	1.5676	0.6243
0.8306	7.0501	1442	1.4917	0.6006
0.4151	8.05	1622	1.4064	0.6420
0.2608	9.0499	1802	1.2911	0.6893
0.1502	10.0499	1982	1.2645	0.6746
0.0901	11.0501	2163	1.2336	0.6805
0.0787	12.05	2343	1.2576	0.6834
0.0635	13.0499	2523	1.2286	0.6834
0.0597	14.0499	2703	1.2249	0.6893

Framework versions

• Transformers 4.46.1
• Pytorch 2.5.1+cu124
• Datasets 3.1.0
• Tokenizers 0.20.1