lang	f1	precision	recall	prevalence	n
cy	1.000000	1.000000	1.000000	0.812500	16
hu	1.000000	1.000000	1.000000	0.529412	17
sv	0.987552	0.975410	1.000000	0.868613	137
no	0.980392	1.000000	0.961538	0.666667	39
de	0.977853	0.972881	0.982877	0.630670	463
da	0.974619	0.989691	0.960000	0.800000	125
en	0.974138	0.974138	0.974138	0.758170	153
it	0.971429	0.980769	0.962264	0.670886	79
fr	0.971429	0.944444	1.000000	0.566667	30
es	0.967742	0.937500	1.000000	0.714286	21
nl	0.966507	0.961905	0.971154	0.675325	154
fi	0.960000	0.923077	1.000000	0.750000	16
pl	0.936170	0.956522	0.916667	0.592593	81
cs	0.933333	0.875000	1.000000	0.411765	17
pt	0.833333	0.714286	1.000000	0.454545	22

Model description

More information needed

Intended uses & limitations

More information needed

More information needed

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall
0.2087	0.9989	437	0.1219	0.9751	0.9806	0.9696
0.1227	2.0	875	0.1591	0.9724	0.9868	0.9584
0.0943	2.9989	1312	0.1554	0.9744	0.9759	0.9728
0.0465	4.0	1750	0.2055	0.9732	0.9868	0.96
0.0339	4.9943	2185	0.1788	0.9759	0.9791	0.9728