learning_rate: 5e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 256
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: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Macro	Recall Macro	F1 Macro	F1 Weighted
2.164	1.0	72	1.0434	0.4483	0.4472	0.4484	0.4398	0.4395
2.0623	2.0	144	0.9968	0.4984	0.5026	0.4994	0.4983	0.4978
1.8507	3.0	216	1.0155	0.5016	0.5522	0.5034	0.4808	0.4802
1.7076	4.0	288	0.9344	0.5721	0.5902	0.5738	0.5572	0.5563
1.4431	5.0	360	0.9258	0.5756	0.5770	0.5768	0.5719	0.5714
1.1592	6.0	432	1.0425	0.5738	0.5831	0.5740	0.5693	0.5691
0.6916	7.0	504	1.2622	0.5659	0.5711	0.5670	0.5640	0.5636
0.3547	8.0	576	1.7560	0.5455	0.5495	0.5452	0.5460	0.5459
0.2534	9.0	648	2.1882	0.5494	0.5620	0.5515	0.5409	0.5401
0.1018	10.0	720	2.3462	0.5645	0.5641	0.5652	0.5633	0.5630
0.0931	11.0	792	2.6256	0.5565	0.5619	0.5582	0.5483	0.5475
0.0504	12.0	864	2.7252	0.5552	0.5570	0.5557	0.5555	0.5551
0.0379	13.0	936	2.9577	0.5517	0.5518	0.5521	0.5518	0.5515
0.0111	14.0	1008	3.2048	0.5614	0.5621	0.5621	0.5609	0.5604
0.0018	15.0	1080	3.3005	0.5610	0.5621	0.5612	0.5616	0.5613
0.0003	16.0	1152	3.3958	0.5610	0.5602	0.5615	0.5605	0.5601
0.0001	17.0	1224	3.4259	0.5623	0.5617	0.5628	0.5620	0.5617
0.0001	18.0	1296	3.4368	0.5619	0.5613	0.5623	0.5616	0.5612
0.0001	19.0	1368	3.4412	0.5619	0.5614	0.5623	0.5616	0.5613
0.0001	20.0	1440	3.4416	0.5623	0.5618	0.5627	0.5621	0.5617

aiface/ModernBERT-base_nli

ModernBERT-base_nli