videomae-base-finetuned-good-gesturePhaseV5

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:

• Accuracy: 0.6871
• Loss: 0.9822
• Accuracy Hold: 0.0
• Accuracy Stroke: 0.0
• Accuracy Recovery: 0.0
• Accuracy Preparation: 0.9221
• Accuracy Unknown: 0.8571

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: 1e-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: 1380

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss	Accuracy Hold	Accuracy Stroke	Accuracy Recovery	Accuracy Preparation	Accuracy Unknown
1.1475	0.0507	70	0.5597	1.2558	0.0	0.0	0.0	1.0	0.0
1.2103	1.0507	140	0.5597	1.2704	0.0	0.0	0.0	1.0	0.0
0.9964	2.0507	210	0.5597	1.2142	0.0	0.0	0.0	1.0	0.0
0.9975	3.0507	280	0.5970	1.0747	0.0	0.0	0.0	0.9733	0.2692
1.0538	4.0507	350	0.6642	0.9622	0.0	0.0	0.0	0.88	0.8846
1.0321	5.0507	420	0.6567	0.9451	0.0	0.0	0.0	0.8533	0.9231
0.7822	6.0507	490	0.7164	0.8797	0.0	0.0	0.0833	0.96	0.8846
0.8743	7.0507	560	0.6791	0.9399	0.0	0.0	0.0833	0.8533	1.0
0.7515	8.0507	630	0.6791	0.9290	0.0	0.0	0.0	0.8667	1.0
0.8525	9.0507	700	0.7090	0.8447	0.0	0.0	0.1667	0.9467	0.8462
0.7661	10.0507	770	0.7090	0.7857	0.0	0.0	0.1667	0.9067	0.9615
0.8363	11.0507	840	0.6866	0.8165	0.0	0.0	0.0833	0.92	0.8462
0.659	12.0507	910	0.7164	0.7951	0.0	0.0	0.1667	0.9067	1.0
0.6274	13.0507	980	0.7015	0.7754	0.0	0.0	0.0833	0.8933	1.0
0.7292	14.0507	1050	0.6791	0.8128	0.0	0.0	0.25	0.8267	1.0
0.7447	15.0507	1120	0.6866	0.7860	0.0	0.0	0.25	0.84	1.0
0.5512	16.0507	1190	0.7015	0.7839	0.0625	0.0	0.1667	0.8667	1.0
0.3404	17.0507	1260	0.7015	0.8055	0.0	0.0	0.3333	0.8533	1.0
0.4406	18.0507	1330	0.6866	0.7800	0.0	0.0	0.1667	0.8533	1.0
0.6358	19.0362	1380	0.7015	0.7816	0.0	0.0	0.1667	0.88	1.0

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1