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: 8640
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
16.1868	0.0333	288	3.7228	0.0391	0.0138	0.0391	0.0127
13.4364	1.0333	576	2.1449	0.4688	0.4296	0.4688	0.3971
3.865	2.0333	864	0.5912	0.8711	0.8732	0.8711	0.8496
1.4285	3.0333	1152	0.3284	0.8867	0.8762	0.8867	0.8663
0.8195	4.0333	1440	0.1833	0.9375	0.9276	0.9375	0.9256
0.4318	5.0333	1728	0.0732	0.9688	0.9756	0.9688	0.9665
0.274	6.0333	2016	0.0440	0.9844	0.9885	0.9844	0.9837
0.2439	7.0333	2304	0.0661	0.9766	0.9792	0.9766	0.9762
0.1427	8.0333	2592	0.0970	0.9805	0.9734	0.9805	0.9752
0.137	9.0333	2880	0.0308	0.9961	0.9969	0.9961	0.9960
0.1534	10.0333	3168	0.0466	0.9883	0.9906	0.9883	0.9881
0.122	11.0333	3456	0.1174	0.9766	0.9784	0.9766	0.9763
0.0199	12.0333	3744	0.0210	0.9922	0.9922	0.9922	0.9922
0.0184	13.0333	4032	0.0467	0.9883	0.9917	0.9883	0.9877
0.1376	14.0333	4320	0.0025	1.0	1.0	1.0	1.0
0.0664	15.0333	4608	0.0323	0.9883	0.9906	0.9883	0.9881
0.1192	16.0333	4896	0.0807	0.9844	0.9885	0.9844	0.9837
0.0246	17.0333	5184	0.0387	0.9922	0.9930	0.9922	0.9921
0.0084	18.0333	5472	0.0339	0.9883	0.9906	0.9883	0.9881
0.0081	19.0333	5760	0.0353	0.9922	0.9938	0.9922	0.9921

Shawon16/VideoMAE_LSA64_SR_12

VideoMAE_LSA64_SR_12