videomae-finetuned-nba-5-class-4-batch-8000-vid-multilabel-4

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:

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.771	0.04	2000	0.7660	0.6227	0.7324	0.2937
0.6225	1.04	4000	0.6446	0.7401	0.8162	0.4653
0.6093	2.04	6000	0.6517	0.7441	0.8223	0.5253
0.603	3.04	8000	0.5630	0.8151	0.8722	0.6558
0.6547	4.04	10000	0.5009	0.8425	0.8911	0.6695
0.6426	5.04	12000	0.5179	0.8422	0.9012	0.6642
0.4447	6.04	14000	0.5052	0.8537	0.8973	0.7147
0.6949	7.04	16000	0.5045	0.8548	0.8974	0.7337
0.509	8.04	18000	0.5262	0.8705	0.9089	0.7768
0.4341	9.04	20000	0.4731	0.8831	0.9163	0.7863
0.5037	10.04	22000	0.5040	0.8781	0.9154	0.7747
0.3592	11.04	24000	0.5091	0.8746	0.9101	0.7821
0.2829	12.04	26000	0.4709	0.8867	0.9230	0.7905
0.3599	13.04	28000	0.4722	0.8888	0.9230	0.7947
0.4152	14.04	30000	0.4744	0.8911	0.9247	0.8074
0.1167	15.04	32000	0.4817	0.8949	0.9241	0.8179
0.2721	16.04	34000	0.4627	0.9064	0.9337	0.8274
0.42	17.04	36000	0.4849	0.8992	0.9282	0.8295
0.5841	18.04	38000	0.4747	0.9026	0.9304	0.8379
0.509	19.04	40000	0.4779	0.8991	0.9273	0.8316
0.1599	20.04	42000	0.4945	0.9056	0.9319	0.8411
0.3645	21.04	44000	0.4875	0.8984	0.9277	0.8242
0.4402	22.04	46000	0.5156	0.9004	0.9283	0.8368
0.2769	23.04	48000	0.5063	0.9028	0.9296	0.8389
0.3009	24.04	50000	0.5122	0.8975	0.9257	0.8326