learning_rate: 3e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
optimizer: Use 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: 3
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
0.3843	0.2088	100	0.2549
0.194	0.4175	200	0.2173
0.1732	0.6263	300	0.2121
0.1696	0.8351	400	0.2007
0.1495	1.0438	500	0.2043
0.1387	1.2526	600	0.2050
0.1362	1.4614	700	0.2051
0.1357	1.6701	800	0.2009
0.128	1.8789	900	0.2027
0.1307	2.0877	1000	0.1997
0.1213	2.2965	1100	0.2024
0.1169	2.5052	1200	0.2034
0.1194	2.7140	1300	0.2034
0.125	2.9228	1400	0.2031

mika5883/ft_rugec_A_c1

ft_rugec_A_c1