learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
2.5504	1.0	734	0.3980	0.8733	0.8720
2.1004	2.0	1468	0.3436	0.8794	0.8766
1.9085	3.0	2202	0.4911	0.8243	0.8186
2.1986	4.0	2936	0.2574	0.8965	0.8941
1.4978	5.0	3670	0.2788	0.8883	0.8806
1.2625	6.0	4404	0.2969	0.8937	0.8935
1.2516	7.0	5138	0.2742	0.8931	0.8884
1.2393	8.0	5872	0.7633	0.6846	0.6681
1.3415	9.0	6606	0.2815	0.8828	0.8752
1.4996	10.0	7340	0.2399	0.8965	0.8917

Haaaaaaaaaax/google-efficientnet-b3-finetuned-kidney_v4

google-efficientnet-b3-finetuned-kidney_v4