videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest

This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
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: 0.05
training_steps: 71400

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.068	0.0100	715	0.3275	0.8850
0.02	1.0100	1430	0.2533	0.9027
0.0049	2.0100	2145	0.3037	0.8947
0.8896	3.0100	2860	0.2705	0.9148
0.5895	4.0100	3575	0.3039	0.8955
0.0007	5.0100	4290	0.2903	0.9124
0.0003	6.0100	5005	0.3106	0.9068
0.0015	7.0100	5720	0.3186	0.9027
0.0003	8.0100	6435	0.4563	0.8818
0.1185	9.0100	7150	0.3532	0.9092
0.0004	10.0100	7865	0.4058	0.9003
0.1368	11.0100	8580	0.3117	0.9220
0.0013	12.0100	9295	0.3217	0.9156
0.0001	13.0100	10010	0.3635	0.9164
0.0017	14.0100	10725	0.3965	0.9124
0.0002	15.0100	11440	0.3649	0.9260
0.0006	16.0100	12155	0.5360	0.8915
0.0001	17.0100	12870	0.4225	0.9132
0.0001	18.0100	13585	0.3639	0.9260
0.0001	19.0100	14300	0.3782	0.9268
0.0002	20.0100	15015	0.3994	0.9156
0.0	21.0100	15730	0.3931	0.9228
0.0002	22.0100	16445	0.4416	0.9148
0.3645	23.0100	17160	0.4689	0.9172
0.0001	24.0100	17875	0.4137	0.9164
0.0001	25.0100	18590	0.3743	0.9260
0.1464	26.0100	19305	0.3404	0.9325
0.0	27.0100	20020	0.4010	0.9220
0.0	28.0100	20735	0.4068	0.9196
0.0001	29.0100	21450	0.3557	0.9317
0.0001	30.0100	22165	0.3854	0.9268
0.0439	31.0100	22880	0.4107	0.9236
0.0001	32.0100	23595	0.3666	0.9309
0.0	33.0100	24310	0.3588	0.9309
0.0001	34.0100	25025	0.3635	0.9317
0.0001	35.0100	25740	0.3691	0.9293
0.0	36.0100	26455	0.3755	0.9293