learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.03
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Roc-auc	Brier	C@1	F1	F05u	Mean
0.1171	0.6748	500	0.1264	0.984	0.956	0.942	0.955	0.955	0.958
0.0899	1.3495	1000	0.0864	0.992	0.97	0.963	0.971	0.971	0.973
0.0498	2.0243	1500	0.0732	0.994	0.976	0.968	0.975	0.971	0.977
0.0716	2.6991	2000	0.0638	0.995	0.979	0.972	0.979	0.977	0.98
0.0672	3.3738	2500	0.0583	0.996	0.98	0.972	0.979	0.98	0.981
0.0453	4.0486	3000	0.0618	0.996	0.98	0.974	0.98	0.977	0.981
0.0785	4.7233	3500	0.0555	0.997	0.979	0.97	0.977	0.983	0.981
0.0467	5.3981	4000	0.0522	0.997	0.982	0.977	0.982	0.981	0.984
0.0672	6.0729	4500	0.0534	0.997	0.983	0.978	0.983	0.981	0.984
0.0249	6.7476	5000	0.0694	0.997	0.979	0.973	0.98	0.972	0.98
0.0227	7.4224	5500	0.0488	0.997	0.983	0.977	0.982	0.983	0.984
0.0261	8.0972	6000	0.0507	0.997	0.983	0.979	0.984	0.982	0.985
0.0654	8.7719	6500	0.0478	0.997	0.983	0.978	0.983	0.984	0.985
0.0291	9.4467	7000	0.0494	0.997	0.984	0.978	0.983	0.982	0.985

MahmoodAnaam/radar-encoder-freeze-pan26

radar-encoder-freeze-pan26