Training Loss	Epoch	Step	Validation Loss	Accuracy	Brier Loss	Nll	F1 Micro	F1 Macro	Ece	Aurc
12767.556	1.0	1000	12472.2930	0.5725	0.5598	2.8765	0.5725	0.5254	0.0980	0.1794
12750.588	2.0	2000	12455.9170	0.6683	0.4822	2.7098	0.6683	0.6534	0.1247	0.1325
12820.858	3.0	3000	12458.1924	0.7003	0.4459	2.6913	0.7003	0.7019	0.1303	0.0964
12762.296	4.0	4000	12445.5703	0.7167	0.4202	2.8379	0.7168	0.7217	0.1078	0.0925
12706.14	5.0	5000	12425.8330	0.753	0.3820	2.7925	0.753	0.7539	0.0997	0.0923
12764.822	6.0	6000	12427.2080	0.7635	0.3603	2.5903	0.7635	0.7659	0.0950	0.0823
12719.869	7.0	7000	12411.4668	0.769	0.3469	2.7566	0.769	0.7761	0.0895	0.0681
12628.481	8.0	8000	12412.3760	0.7738	0.3535	2.7667	0.7738	0.7832	0.1127	0.0699
12624.542	9.0	9000	12396.7773	0.7933	0.3243	2.4484	0.7932	0.7954	0.1002	0.0664
12681.642	10.0	10000	12391.2744	0.7943	0.3241	2.5709	0.7943	0.7979	0.1081	0.0592
12656.593	11.0	11000	12383.5020	0.8015	0.3190	2.4516	0.8015	0.8065	0.1064	0.0597
12638.155	12.0	12000	12372.9707	0.7957	0.3357	2.4891	0.7957	0.7956	0.1225	0.0679
12698.474	13.0	13000	12370.7217	0.813	0.2988	2.1414	0.813	0.8125	0.1030	0.0494
12574.549	14.0	14000	12361.6641	0.8045	0.3218	2.4610	0.8045	0.8043	0.1155	0.0560
12589.537	15.0	15000	12345.1123	0.8193	0.3046	2.2566	0.8193	0.8184	0.1220	0.0524
12592.604	16.0	16000	12354.9756	0.817	0.3078	2.3526	0.817	0.8207	0.1204	0.0527
12660.709	17.0	17000	12334.7686	0.8293	0.2942	2.2857	0.8293	0.8284	0.1201	0.0482
12591.369	18.0	18000	12334.4570	0.829	0.2948	2.1559	0.8290	0.8287	0.1211	0.0451
12598.469	19.0	19000	12320.7510	0.826	0.2997	2.2348	0.826	0.8251	0.1240	0.0473
12497.537	20.0	20000	12307.0811	0.8347	0.2833	2.2433	0.8347	0.8358	0.1200	0.0426
12537.66	21.0	21000	12310.8438	0.8323	0.2965	2.1513	0.8323	0.8321	0.1287	0.0490
12524.668	22.0	22000	12300.1055	0.8403	0.2776	2.1780	0.8403	0.8407	0.1207	0.0427
12433.952	23.0	23000	12288.1221	0.8353	0.2898	2.2189	0.8353	0.8357	0.1346	0.0439
12598.38	24.0	24000	12282.6680	0.8442	0.2765	2.1653	0.8443	0.8440	0.1264	0.0438
12474.447	25.0	25000	12277.6797	0.8363	0.2925	2.1209	0.8363	0.8350	0.1366	0.0451
12522.706	26.0	26000	12276.4502	0.8465	0.2764	2.0779	0.8465	0.8469	0.1291	0.0432
12502.289	27.0	27000	12268.1758	0.8445	0.2811	2.0839	0.8445	0.8442	0.1318	0.0465
12465.994	28.0	28000	12252.7266	0.8433	0.2882	2.1410	0.8433	0.8431	0.1380	0.0479
12467.13	29.0	29000	12260.4912	0.8442	0.2838	2.1129	0.8443	0.8430	0.1348	0.0487
12540.006	30.0	30000	12249.1670	0.846	0.2811	2.1134	0.8460	0.8458	0.1349	0.0486
12594.326	31.0	31000	12245.6699	0.8452	0.2850	2.0734	0.8452	0.8443	0.1363	0.0480
12486.203	32.0	32000	12240.5479	0.8468	0.2813	2.0757	0.8468	0.8463	0.1353	0.0484
12468.631	33.0	33000	12231.9600	0.852	0.2715	2.0178	0.852	0.8523	0.1309	0.0450
12423.715	34.0	34000	12215.6680	0.8472	0.2843	2.0927	0.8472	0.8470	0.1389	0.0491
12454.715	35.0	35000	12223.0361	0.8492	0.2772	2.0161	0.8492	0.8485	0.1340	0.0476
12466.932	36.0	36000	12221.3887	0.8495	0.2776	2.0135	0.8495	0.8488	0.1343	0.0467
12483.745	37.0	37000	12210.9414	0.8508	0.2748	2.0374	0.8508	0.8506	0.1350	0.0493
12453.102	38.0	38000	12224.9482	0.852	0.2737	1.9699	0.852	0.8517	0.1308	0.0460
12511.225	39.0	39000	12213.9756	0.8522	0.2763	1.9619	0.8522	0.8518	0.1342	0.0484
12561.782	40.0	40000	12213.9297	0.852	0.2736	2.0481	0.852	0.8516	0.1326	0.0477
12524.982	41.0	41000	12208.1758	0.8518	0.2745	1.9751	0.8518	0.8509	0.1346	0.0490
12465.351	42.0	42000	12215.3604	0.8532	0.2730	2.0037	0.8532	0.8521	0.1314	0.0474
12419.902	43.0	43000	12211.3701	0.8565	0.2680	2.0140	0.8565	0.8561	0.1297	0.0462
12493.264	44.0	44000	12196.7217	0.8532	0.2717	1.9866	0.8532	0.8524	0.1336	0.0487
12487.514	45.0	45000	12199.4902	0.8532	0.2700	1.9711	0.8532	0.8523	0.1309	0.0478
12321.575	46.0	46000	12189.0117	0.8535	0.2727	2.0220	0.8535	0.8528	0.1335	0.0492
12423.494	47.0	47000	12198.2002	0.8542	0.2711	1.9648	0.8542	0.8536	0.1331	0.0478
12535.605	48.0	48000	12192.7061	0.8565	0.2678	2.0098	0.8565	0.8560	0.1292	0.0489
12319.588	49.0	49000	12185.3916	0.856	0.2691	2.0285	0.856	0.8554	0.1311	0.0506
12470.527	50.0	50000	12194.7598	0.8558	0.2688	1.9967	0.8558	0.8552	0.1305	0.0490

Framework versions

Transformers 4.26.1
Pytorch 1.13.1.post200
Datasets 2.9.0
Tokenizers 0.13.2

jordyvl/dit-base-finetuned-rvlcdip-small_rvl_cdip-NK1000_og_simkd

dit-base-finetuned-rvlcdip-small_rvl_cdip-NK1000_og_simkd

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jordyvl/
dit-base-finetuned-rvlcdip-small_rvl_cdip-NK1000_og_simkd