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
0.2243	1.0776	500	0.3152	0.946	0.898	0.85	0.83	0.912	0.887
0.2362	2.1552	1000	0.2601	0.958	0.919	0.887	0.881	0.923	0.914
0.1790	3.2328	1500	0.2396	0.963	0.926	0.9	0.895	0.929	0.923
0.2652	4.3103	2000	0.2677	0.965	0.916	0.885	0.875	0.934	0.915
0.1927	5.3879	2500	0.2230	0.968	0.932	0.906	0.908	0.908	0.925
0.1476	6.4655	3000	0.2172	0.971	0.933	0.908	0.905	0.936	0.931
0.2706	7.5431	3500	0.2093	0.971	0.936	0.913	0.913	0.928	0.932
0.1720	8.6207	4000	0.2072	0.972	0.937	0.914	0.913	0.929	0.933
0.1574	9.6983	4500	0.2077	0.972	0.937	0.914	0.913	0.931	0.933

MahmoodAnaam/radar-encoder-freeze-raid

radar-encoder-freeze-raid