Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	10.8614	-0.0184	10.8589	3.2953
No log	2.0	4	8.4191	0.0	8.4172	2.9012
No log	3.0	6	6.6297	0.0	6.6279	2.5745
No log	4.0	8	5.3937	0.0214	5.3922	2.3221
6.3927	5.0	10	4.1538	0.0040	4.1528	2.0378
6.3927	6.0	12	3.2957	0.0	3.2948	1.8152
6.3927	7.0	14	2.4521	-0.0010	2.4516	1.5658
6.3927	8.0	16	1.9714	0.0583	1.9711	1.4040
6.3927	9.0	18	1.6013	0.0211	1.6013	1.2654
2.5059	10.0	20	1.3405	0.0315	1.3405	1.1578
2.5059	11.0	22	1.1218	0.0211	1.1219	1.0592
2.5059	12.0	24	1.0945	0.0211	1.0946	1.0462
2.5059	13.0	26	1.0649	0.0315	1.0649	1.0319
2.5059	14.0	28	1.2687	0.0850	1.2687	1.1263
1.8719	15.0	30	1.1433	0.0850	1.1433	1.0692
1.8719	16.0	32	0.8401	0.1509	0.8401	0.9166
1.8719	17.0	34	0.8186	0.2195	0.8186	0.9048
1.8719	18.0	36	0.9338	0.1857	0.9340	0.9664
1.8719	19.0	38	0.7695	0.3424	0.7696	0.8773
1.5022	20.0	40	0.6722	0.4726	0.6723	0.8199
1.5022	21.0	42	0.6753	0.4500	0.6754	0.8218
1.5022	22.0	44	0.6858	0.4622	0.6859	0.8282
1.5022	23.0	46	0.6326	0.4930	0.6327	0.7954
1.5022	24.0	48	0.6385	0.4574	0.6386	0.7991
0.9617	25.0	50	0.6275	0.4213	0.6276	0.7922
0.9617	26.0	52	0.6438	0.3934	0.6439	0.8024
0.9617	27.0	54	0.6524	0.4026	0.6524	0.8077
0.9617	28.0	56	0.6454	0.4179	0.6454	0.8034
0.9617	29.0	58	0.6138	0.4535	0.6137	0.7834
0.4751	30.0	60	0.6470	0.4291	0.6469	0.8043
0.4751	31.0	62	0.6725	0.4673	0.6724	0.8200
0.4751	32.0	64	0.6473	0.4730	0.6472	0.8045
0.4751	33.0	66	0.6675	0.4567	0.6675	0.8170
0.4751	34.0	68	0.6707	0.4434	0.6706	0.8189
0.2893	35.0	70	0.6846	0.4576	0.6844	0.8273
0.2893	36.0	72	0.6887	0.4563	0.6885	0.8298
0.2893	37.0	74	0.7709	0.3849	0.7707	0.8779
0.2893	38.0	76	0.7877	0.4168	0.7875	0.8874
0.2893	39.0	78	0.7849	0.4369	0.7847	0.8858
0.1895	40.0	80	0.7293	0.4505	0.7292	0.8539
0.1895	41.0	82	0.7162	0.4879	0.7160	0.8462
0.1895	42.0	84	0.6753	0.5079	0.6751	0.8216
0.1895	43.0	86	0.6610	0.4997	0.6608	0.8129
0.1895	44.0	88	0.7175	0.5060	0.7173	0.8469
0.1498	45.0	90	0.7117	0.5063	0.7114	0.8434
0.1498	46.0	92	0.6688	0.4791	0.6686	0.8177
0.1498	47.0	94	0.6862	0.4532	0.6860	0.8283
0.1498	48.0	96	0.7625	0.4525	0.7622	0.8731
0.1498	49.0	98	0.7614	0.4568	0.7612	0.8725
0.1158	50.0	100	0.7075	0.4509	0.7074	0.8411
0.1158	51.0	102	0.6898	0.4680	0.6896	0.8304
0.1158	52.0	104	0.7981	0.4433	0.7978	0.8932
0.1158	53.0	106	0.7124	0.4744	0.7121	0.8439
0.1158	54.0	108	0.6927	0.4590	0.6924	0.8321
0.1042	55.0	110	0.7329	0.4773	0.7326	0.8559
0.1042	56.0	112	0.8818	0.4421	0.8814	0.9388
0.1042	57.0	114	0.7754	0.4532	0.7751	0.8804
0.1042	58.0	116	0.7168	0.4430	0.7165	0.8465
0.1042	59.0	118	0.7118	0.4700	0.7115	0.8435
0.1073	60.0	120	0.8100	0.4589	0.8097	0.8998
0.1073	61.0	122	0.7436	0.4583	0.7433	0.8622
0.1073	62.0	124	0.6811	0.4849	0.6809	0.8252
0.1073	63.0	126	0.6990	0.4926	0.6987	0.8359
0.1073	64.0	128	0.8287	0.4602	0.8283	0.9101
0.0959	65.0	130	0.7818	0.4676	0.7815	0.8840
0.0959	66.0	132	0.6849	0.4970	0.6846	0.8274
0.0959	67.0	134	0.6759	0.5080	0.6756	0.8219
0.0959	68.0	136	0.7375	0.4836	0.7371	0.8586
0.0959	69.0	138	0.7338	0.4749	0.7335	0.8564
0.0929	70.0	140	0.6739	0.4918	0.6737	0.8208
0.0929	71.0	142	0.6971	0.4723	0.6968	0.8348
0.0929	72.0	144	0.7721	0.4548	0.7718	0.8785
0.0929	73.0	146	0.7851	0.4629	0.7848	0.8859
0.0929	74.0	148	0.7054	0.4752	0.7051	0.8397
0.0761	75.0	150	0.6794	0.5014	0.6791	0.8241
0.0761	76.0	152	0.6964	0.4838	0.6962	0.8344
0.0761	77.0	154	0.7463	0.4830	0.7460	0.8637
0.0761	78.0	156	0.7453	0.4728	0.7450	0.8631
0.0761	79.0	158	0.7094	0.4781	0.7091	0.8421
0.0794	80.0	160	0.7005	0.4825	0.7003	0.8368
0.0794	81.0	162	0.6873	0.4886	0.6870	0.8289
0.0794	82.0	164	0.6524	0.5189	0.6522	0.8076
0.0794	83.0	166	0.6452	0.5359	0.6449	0.8031
0.0794	84.0	168	0.6434	0.5221	0.6431	0.8020
0.0714	85.0	170	0.6550	0.5278	0.6547	0.8092
0.0714	86.0	172	0.6943	0.5023	0.6940	0.8331
0.0714	87.0	174	0.7244	0.4848	0.7242	0.8510
0.0714	88.0	176	0.7211	0.4829	0.7208	0.8490
0.0714	89.0	178	0.7320	0.4729	0.7317	0.8554
0.0627	90.0	180	0.7548	0.4780	0.7545	0.8686
0.0627	91.0	182	0.7719	0.4701	0.7716	0.8784
0.0627	92.0	184	0.7645	0.4721	0.7641	0.8741
0.0627	93.0	186	0.7452	0.4844	0.7449	0.8631
0.0627	94.0	188	0.7253	0.4928	0.7250	0.8515
0.0626	95.0	190	0.7218	0.5008	0.7215	0.8494
0.0626	96.0	192	0.7172	0.4964	0.7168	0.8467
0.0626	97.0	194	0.7111	0.4923	0.7108	0.8431
0.0626	98.0	196	0.7105	0.4929	0.7101	0.8427
0.0626	99.0	198	0.7125	0.4908	0.7121	0.8439
0.0574	100.0	200	0.7129	0.4908	0.7126	0.8442

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

genki10/ASAP_FineTuningBERT_AugV7_k2_task1_organization_fold1

ASAP_FineTuningBERT_AugV7_k2_task1_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV7_k2_task1_organization_fold1