learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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
num_epochs: 1
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.0616	0.0667	500	0.8034	0.1604
0.0299	0.1333	1000	0.9175	0.0660
0.025	0.2	1500	0.8977	0.0927
0.0214	0.2667	2000	0.9478	0.0440
0.0197	0.3333	2500	0.8927	0.1201
0.018	0.4	3000	0.9510	0.0436
0.0163	0.4667	3500	0.9623	0.0352
0.0152	0.5333	4000	0.936	0.0679
0.0132	0.6	4500	0.8901	0.1139
0.0127	0.6667	5000	0.9468	0.0523
0.0113	0.7333	5500	0.9455	0.0515
0.0113	0.8	6000	0.9580	0.0387
0.0091	0.8667	6500	0.9319	0.0847
0.0107	0.9333	7000	0.9407	0.0630
0.0102	1.0	7500	0.9553	0.0432

Yuvrajg2107/deberta-v3-hybrid-detector_12

deberta-v3-hybrid-detector_12