learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
num_epochs: 5
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall
0.8435	0.0985	500	0.1890	0.9233	0.9064	0.9408
0.4494	0.1970	1000	0.1712	0.9200	0.9528	0.8895
0.3570	0.2955	1500	0.1289	0.9490	0.9565	0.9416
0.3408	0.3940	2000	0.1185	0.9605	0.9487	0.9725
0.3233	0.4926	2500	0.1407	0.9527	0.9615	0.9440
0.2669	0.5911	3000	0.1390	0.9672	0.9500	0.9851
0.2770	0.6896	3500	0.1290	0.9636	0.9626	0.9646
0.2880	0.7881	4000	0.0926	0.9718	0.9600	0.9839
0.2141	0.8866	4500	0.1125	0.9615	0.9637	0.9594
0.2006	0.9851	5000	0.0959	0.9722	0.9599	0.9848
0.1123	1.0835	5500	0.1256	0.9694	0.9668	0.9721
0.0837	1.1821	6000	0.1346	0.9708	0.9521	0.9901
0.1683	1.2806	6500	0.0773	0.9752	0.9638	0.9869
0.1697	1.3791	7000	0.0913	0.9740	0.9678	0.9802
0.1300	1.4776	7500	0.0865	0.9745	0.9631	0.9862
0.1412	1.5761	8000	0.0931	0.9747	0.9579	0.9922

OliverArt5500/klasyfikatorspamu1

klasyfikatorspamu1