Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.7031	0.56	500	0.3041	0.6755	0.6917	0.6835	0.9328
0.2981	1.11	1000	0.2336	0.7821	0.8011	0.7915	0.9489
0.2327	1.67	1500	0.1969	0.8030	0.7947	0.7988	0.9518
0.1962	2.22	2000	0.1898	0.8152	0.8501	0.8323	0.9583
0.1683	2.78	2500	0.1690	0.8053	0.8401	0.8223	0.9585
0.1499	3.33	3000	0.1810	0.8319	0.8444	0.8381	0.9602
0.1376	3.89	3500	0.1888	0.8340	0.8591	0.8464	0.9599
0.1198	4.44	4000	0.2022	0.8089	0.8494	0.8287	0.9570
0.1089	5.0	4500	0.1930	0.8320	0.8448	0.8383	0.9578
0.0911	5.56	5000	0.1945	0.8412	0.8544	0.8478	0.9627
0.0945	6.11	5500	0.1961	0.8424	0.8430	0.8427	0.9606
0.0695	6.67	6000	0.2186	0.8289	0.8559	0.8422	0.9588
0.0628	7.22	6500	0.2016	0.8567	0.8723	0.8644	0.9629
0.0563	7.78	7000	0.2195	0.8528	0.8727	0.8626	0.9617
0.0504	8.33	7500	0.2301	0.8508	0.8730	0.8618	0.9609
0.0444	8.89	8000	0.2135	0.8486	0.8780	0.8631	0.9629
0.0386	9.44	8500	0.2347	0.8451	0.8838	0.8640	0.9625
0.0355	10.0	9000	0.2314	0.8499	0.8670	0.8584	0.9620
0.0305	10.56	9500	0.2467	0.8532	0.8709	0.8619	0.9627
0.0283	11.11	10000	0.2602	0.8440	0.8687	0.8562	0.9615
0.0217	11.67	10500	0.2639	0.8548	0.8777	0.8661	0.9632
0.0224	12.22	11000	0.2688	0.8504	0.8780	0.8640	0.9623
0.0194	12.78	11500	0.2661	0.8545	0.8798	0.8670	0.9629
0.0224	13.33	12000	0.2731	0.8512	0.8798	0.8653	0.9623
0.014	13.89	12500	0.2778	0.8537	0.8766	0.8650	0.9629
0.0146	14.44	13000	0.2783	0.8551	0.8798	0.8673	0.9629
0.0142	15.0	13500	0.2807	0.8544	0.8813	0.8676	0.9631

stulcrad/CNEC2_0_xlm-roberta-large

CNEC2_0_xlm-roberta-large