videomae-base-groub2-finetuned-SLT-subset

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: 0.2405
• Accuracy: 1.0

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: 960

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.928	0.06	61	3.6624	0.0244
3.8332	1.06	122	3.5354	0.0732
3.5587	2.06	183	3.2996	0.0976
3.4907	3.06	244	3.1796	0.0976
3.4674	4.06	305	3.1159	0.0976
3.5079	5.06	366	3.0202	0.1220
2.9034	6.06	427	2.8292	0.1707
2.9286	7.06	488	2.4582	0.6098
2.4388	8.06	549	1.8469	0.7317
1.7172	9.06	610	1.2915	0.8537
1.2504	10.06	671	0.8991	0.9512
0.974	11.06	732	0.5943	0.9268
0.4528	12.06	793	0.4040	0.9512
0.3593	13.06	854	0.3052	1.0
0.2068	14.06	915	0.2569	1.0
0.185	15.05	960	0.2405	1.0

Framework versions

• Transformers 4.33.3
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3