learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
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_ratio: 0.06
num_epochs: 4

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Accuracy Balanced	F1 Micro	Precision Macro	Recall Macro	Precision Micro	Recall Micro
0.2312	0.7353	500	0.1702	0.9595	0.4897	0.5	0.9595	0.4798	0.5	0.9595	0.9595
0.1558	1.4706	1000	0.0969	0.9757	0.7949	0.7261	0.9757	0.9352	0.7261	0.9757	0.9757
0.1042	2.2059	1500	0.1112	0.9706	0.8199	0.8366	0.9706	0.8049	0.8366	0.9706	0.9706
0.0622	2.9412	2000	0.1319	0.9757	0.7996	0.7348	0.9757	0.9224	0.7348	0.9757	0.9757
0.0499	3.6765	2500	0.0968	0.9823	0.8778	0.8515	0.9823	0.9088	0.8515	0.9823	0.9823

mljn/mdeberta-v3-base-finetuned-renewable-energy-classification

mdeberta-v3-base-finetuned-renewable-energy-classification