learning_rate: 3e-05
train_batch_size: 16
eval_batch_size: 2
seed: 42
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: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	12	0.0787	0.7965	0.7679	0.7819	0.9814
No log	2.0	24	0.0585	0.7896	0.8328	0.8106	0.9830
No log	3.0	36	0.0404	0.8902	0.8720	0.8810	0.9894
No log	4.0	48	0.0399	0.8286	0.8908	0.8586	0.9877
No log	5.0	60	0.0357	0.8984	0.8754	0.8868	0.9909
No log	6.0	72	0.0359	0.8709	0.8976	0.8840	0.9905
No log	7.0	84	0.0401	0.8670	0.9232	0.8942	0.9904
No log	8.0	96	0.0388	0.8585	0.9113	0.8841	0.9904
No log	9.0	108	0.0395	0.8891	0.9027	0.8959	0.9907
No log	10.0	120	0.0381	0.885	0.9061	0.8954	0.9914
No log	11.0	132	0.0384	0.8725	0.9113	0.8915	0.9911
No log	12.0	144	0.0400	0.8781	0.9096	0.8935	0.9909
No log	13.0	156	0.0402	0.8918	0.9147	0.9031	0.9919
No log	14.0	168	0.0393	0.8940	0.9215	0.9076	0.9921
No log	15.0	180	0.0415	0.8935	0.9164	0.9048	0.9916
No log	16.0	192	0.0392	0.8961	0.9130	0.9045	0.9919
No log	17.0	204	0.0406	0.8809	0.9215	0.9008	0.9916
No log	18.0	216	0.0414	0.8847	0.9164	0.9003	0.9917
No log	19.0	228	0.0418	0.8865	0.9198	0.9028	0.9918
No log	20.0	240	0.0419	0.8882	0.9215	0.9045	0.9919

TomasFAV/LiLTInvoiceCzechV0123

LiLTInvoiceCzechV0123Test