learning_rate: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	80	0.6962	0.6924	0.7009	0.6924	0.6672
0.8725	2.0	160	0.5648	0.7711	0.8219	0.7711	0.7728
0.8725	3.0	240	0.4637	0.8244	0.8342	0.8244	0.8249
0.3152	4.0	320	0.3919	0.8413	0.8415	0.8413	0.8405
0.3152	5.0	400	0.4121	0.8764	0.8848	0.8764	0.8778
0.1611	6.0	480	0.2989	0.8876	0.8923	0.8876	0.8881
0.1611	7.0	560	0.6423	0.8244	0.8607	0.8244	0.8278
0.1022	8.0	640	0.3978	0.8764	0.8787	0.8764	0.8769
0.1022	9.0	720	0.5891	0.8624	0.8765	0.8624	0.8638

lyfesan/vit-brats-artifact-classifier

vit-brats-artifact-classifier