learning_rate: 1e-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	20	0.1056	0.7803	0.84	0.8091	0.9716
No log	2.0	40	0.0831	0.8105	0.8901	0.8484	0.9764
No log	3.0	60	0.0704	0.8410	0.8994	0.8692	0.9804
No log	4.0	80	0.0675	0.8403	0.9095	0.8736	0.9808
No log	5.0	100	0.0632	0.8630	0.8932	0.8779	0.9821
No log	6.0	120	0.0706	0.8319	0.9111	0.8697	0.9800
No log	7.0	140	0.0611	0.8729	0.8932	0.8829	0.9834
No log	8.0	160	0.0608	0.8754	0.9056	0.8902	0.9835
No log	9.0	180	0.0595	0.8769	0.9243	0.9000	0.9848
No log	10.0	200	0.0606	0.8759	0.9153	0.8952	0.9842
No log	11.0	220	0.0610	0.8855	0.9192	0.9021	0.9850
No log	12.0	240	0.0632	0.8720	0.9258	0.8981	0.9844
No log	13.0	260	0.0608	0.8961	0.9115	0.9037	0.9853
No log	14.0	280	0.0610	0.8953	0.9165	0.9058	0.9855
No log	15.0	300	0.0615	0.8874	0.9181	0.9025	0.9853
No log	16.0	320	0.0627	0.8841	0.9216	0.9025	0.9851
No log	17.0	340	0.0625	0.8807	0.92	0.8999	0.9847
No log	18.0	360	0.0612	0.8944	0.9177	0.9059	0.9856
No log	19.0	380	0.0619	0.8893	0.92	0.9044	0.9854
No log	20.0	400	0.0618	0.8901	0.9212	0.9053	0.9856

TomasFAV/BERTInvoiceCzechV0123

BERTInvoiceCzechV0123Test