learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use OptimizerNames.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
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
4.1358	1.0	157	3.9867	0.328	0.3446
2.5658	2.0	314	2.4812	0.71	0.7205
1.5019	3.0	471	1.4903	0.806	0.8127
1.1238	4.0	628	0.9173	0.834	0.8377
1.0664	5.0	785	0.6943	0.8793	0.8803
0.8955	6.0	942	0.6340	0.8847	0.8874
0.8461	7.0	1099	0.5398	0.8907	0.8934
0.841	8.0	1256	0.5054	0.88	0.8863
0.8	9.0	1413	0.5278	0.9	0.9042
0.7614	9.9408	1560	0.5160	0.896	0.9002

Haaaaaaaaaax/efficientnet-b3-finetuned-food101

efficientnet-b3-finetuned-food101