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: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Macro	Recall Macro	F1 Macro	F1 Weighted
1.2139	1.0	90	0.5024	0.8073	0.8182	0.5993	0.6061	0.7934
0.6774	2.0	180	0.2870	0.9033	0.8421	0.7140	0.7451	0.8960
0.4571	3.0	270	0.3474	0.8920	0.8074	0.6669	0.6824	0.8802
0.2925	4.0	360	0.3089	0.9065	0.8778	0.7074	0.7413	0.8977
0.1725	5.0	450	0.3611	0.8958	0.7729	0.7574	0.7646	0.8946
0.0977	6.0	540	0.4743	0.9090	0.8405	0.7388	0.7695	0.9036
0.0576	7.0	630	0.6044	0.8743	0.7234	0.8019	0.7413	0.8878
0.0338	8.0	720	0.6118	0.9040	0.7756	0.7506	0.7615	0.9019
0.016	9.0	810	0.6754	0.9071	0.8334	0.7379	0.7670	0.9019
0.0113	10.0	900	0.6732	0.9065	0.7898	0.7606	0.7733	0.9044
0.0065	11.0	990	0.7871	0.9046	0.8046	0.7277	0.7519	0.8992
0.0037	12.0	1080	0.7134	0.9109	0.7989	0.7147	0.7386	0.9038
0.0022	13.0	1170	0.7784	0.9015	0.7765	0.7383	0.7529	0.8982
0.0013	14.0	1260	0.7176	0.9109	0.7832	0.7486	0.7625	0.9079
0.0011	15.0	1350	0.7681	0.9059	0.7920	0.7371	0.7565	0.9017
0.0001	16.0	1440	0.7170	0.9071	0.7833	0.7282	0.7479	0.9024
0.0007	17.0	1530	0.7219	0.9109	0.8022	0.7442	0.7652	0.9068
0.0003	18.0	1620	0.7379	0.9103	0.7950	0.7398	0.7596	0.9060
0.0006	19.0	1710	0.7198	0.9116	0.8074	0.7404	0.7635	0.9068
0.0004	20.0	1800	0.7185	0.9116	0.8041	0.7362	0.7592	0.9065

aiface/modernBert-base_v2

modernBert-base_v2