learning_rate: 5e-05
train_batch_size: 256
eval_batch_size: 256
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
num_epochs: 3

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.7609	0.1667	20	0.2774	0.8618	0.5589	0.6059	0.5814
0.1981	0.3333	40	0.1765	0.9260	0.9647	0.8484	0.8954
0.1699	0.5	60	0.1754	0.9264	0.9650	0.8497	0.8963
0.1715	0.6667	80	0.1773	0.9264	0.9650	0.8497	0.8963
0.1727	0.8333	100	0.1744	0.9264	0.9650	0.8497	0.8963
0.1717	1.0	120	0.1759	0.9264	0.9650	0.8497	0.8963
0.1717	1.1667	140	0.1741	0.9264	0.9650	0.8497	0.8963
0.1649	1.3333	160	0.1732	0.9264	0.9650	0.8497	0.8963
0.174	1.5	180	0.1769	0.9264	0.9650	0.8497	0.8963
0.1472	1.6667	200	0.1740	0.9264	0.9650	0.8497	0.8963
0.1725	1.8333	220	0.1733	0.9264	0.9650	0.8497	0.8963
0.1693	2.0	240	0.1738	0.9264	0.9650	0.8497	0.8963
0.1705	2.1667	260	0.1733	0.9264	0.9650	0.8497	0.8963
0.1761	2.3333	280	0.1739	0.9264	0.9650	0.8497	0.8963
0.1608	2.5	300	0.1738	0.9264	0.9650	0.8497	0.8963
0.1593	2.6667	320	0.1739	0.9264	0.9650	0.8497	0.8963
0.1568	2.8333	340	0.1737	0.9264	0.9650	0.8497	0.8963
0.1675	3.0	360	0.1735	0.9264	0.9650	0.8497	0.8963

sterbanger/absa-roberta-model

absa-roberta-model