learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 128
seed: 42
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_steps: 50
num_epochs: 4

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2935	0.2769	250	0.2018	0.9763	0.9763
0.1594	0.5537	500	0.1717	0.9776	0.9776
0.1662	0.8306	750	0.1184	0.9844	0.9844
0.0709	1.1074	1000	0.1548	0.9844	0.9844
0.0810	1.3843	1250	0.1246	0.9857	0.9857
0.0799	1.6611	1500	0.1152	0.9863	0.9863
0.0720	1.9380	1750	0.1242	0.9869	0.9869
0.0279	2.2148	2000	0.1691	0.9844	0.9844
0.0228	2.4917	2250	0.1072	0.9913	0.9913
0.0184	2.7685	2500	0.1114	0.9906	0.9906
0.0173	3.0454	2750	0.1519	0.9894	0.9894

pankajrudra/MediBool-banglabert-Context_Aware

MediBool-banglabert-Context_Aware