learning_rate: 5e-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use 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
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.2701	1.0	145	0.0343	0.8090	0.9874	0.8893
0.2554	2.0	290	0.0354	0.9163	0.9769	0.9456
0.0511	3.0	435	0.0548	0.9588	0.9769	0.9677
0.0611	4.0	580	0.0677	0.9568	0.9779	0.9673
0.0649	5.0	725	0.0684	0.9729	0.9821	0.9775
0.0055	6.0	870	0.0791	0.9779	0.9748	0.9763
0.0082	7.0	1015	0.0738	0.9768	0.9737	0.9753
0.0094	8.0	1160	0.0709	0.9770	0.9800	0.9785
0.0069	9.0	1305	0.0711	0.9841	0.9779	0.9810
0.0003	10.0	1450	0.0705	0.9820	0.9769	0.9795

buddhadeb33/output_dinov2_v1_focal_loss

output_dinov2_v1_focal_loss