Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	11.7865	-0.0246	11.7861	3.4331
No log	2.0	4	9.3046	0.0005	9.3043	3.0503
No log	3.0	6	7.4317	0.0	7.4314	2.7261
No log	4.0	8	6.0107	0.0228	6.0104	2.4516
7.0816	5.0	10	4.6787	0.0064	4.6785	2.1630
7.0816	6.0	12	3.6801	0.0	3.6800	1.9183
7.0816	7.0	14	2.9044	0.0	2.9043	1.7042
7.0816	8.0	16	2.2033	0.1237	2.2032	1.4843
7.0816	9.0	18	1.7473	0.0213	1.7473	1.3219
2.7452	10.0	20	1.4010	0.0107	1.4012	1.1837
2.7452	11.0	22	1.1931	0.0107	1.1933	1.0924
2.7452	12.0	24	1.1085	0.0174	1.1087	1.0530
2.7452	13.0	26	0.9492	0.0241	0.9494	0.9744
2.7452	14.0	28	1.0373	0.1070	1.0374	1.0185
1.8593	15.0	30	0.8817	0.2338	0.8820	0.9391
1.8593	16.0	32	0.9054	0.2298	0.9057	0.9517
1.8593	17.0	34	0.7933	0.3223	0.7937	0.8909
1.8593	18.0	36	0.6941	0.4139	0.6944	0.8333
1.8593	19.0	38	0.6914	0.4335	0.6917	0.8317
1.3842	20.0	40	0.8388	0.3172	0.8393	0.9161
1.3842	21.0	42	0.7565	0.2564	0.7569	0.8700
1.3842	22.0	44	0.7868	0.2312	0.7873	0.8873
1.3842	23.0	46	0.8483	0.2416	0.8489	0.9213
1.3842	24.0	48	0.6920	0.3478	0.6925	0.8322
0.9146	25.0	50	0.6228	0.3473	0.6232	0.7895
0.9146	26.0	52	0.6024	0.4423	0.6029	0.7765
0.9146	27.0	54	0.6425	0.4266	0.6430	0.8019
0.9146	28.0	56	0.6942	0.3519	0.6948	0.8335
0.9146	29.0	58	0.7996	0.4132	0.8000	0.8944
0.4855	30.0	60	0.7451	0.4620	0.7455	0.8634
0.4855	31.0	62	0.6851	0.4758	0.6855	0.8280
0.4855	32.0	64	0.6966	0.4540	0.6970	0.8349
0.4855	33.0	66	0.6997	0.4592	0.7000	0.8367
0.4855	34.0	68	0.7456	0.4523	0.7458	0.8636
0.2386	35.0	70	0.7811	0.4135	0.7814	0.8840
0.2386	36.0	72	0.8926	0.3974	0.8929	0.9449
0.2386	37.0	74	0.8151	0.4153	0.8154	0.9030
0.2386	38.0	76	0.9334	0.4077	0.9336	0.9662
0.2386	39.0	78	0.7477	0.4522	0.7480	0.8649
0.1999	40.0	80	0.9344	0.4366	0.9347	0.9668
0.1999	41.0	82	0.7677	0.4440	0.7680	0.8763
0.1999	42.0	84	0.6746	0.4869	0.6748	0.8215
0.1999	43.0	86	0.6700	0.5092	0.6703	0.8187
0.1999	44.0	88	0.8012	0.4505	0.8015	0.8953
0.1897	45.0	90	0.7161	0.4586	0.7165	0.8464
0.1897	46.0	92	0.7106	0.4656	0.7109	0.8432
0.1897	47.0	94	0.6774	0.4706	0.6777	0.8232
0.1897	48.0	96	0.6788	0.4662	0.6791	0.8241
0.1897	49.0	98	0.6613	0.4453	0.6617	0.8134
0.1144	50.0	100	0.6942	0.4748	0.6945	0.8334
0.1144	51.0	102	0.6565	0.5035	0.6567	0.8104
0.1144	52.0	104	0.6477	0.5236	0.6479	0.8049
0.1144	53.0	106	0.6663	0.4898	0.6666	0.8164
0.1144	54.0	108	0.6327	0.5062	0.6329	0.7956
0.089	55.0	110	0.6141	0.4811	0.6143	0.7838
0.089	56.0	112	0.6899	0.4761	0.6902	0.8308
0.089	57.0	114	0.7257	0.4524	0.7259	0.8520
0.089	58.0	116	0.6412	0.4744	0.6414	0.8009
0.089	59.0	118	0.6530	0.4789	0.6533	0.8083
0.0927	60.0	120	0.7460	0.4584	0.7463	0.8639
0.0927	61.0	122	0.7504	0.4646	0.7507	0.8664
0.0927	62.0	124	0.6363	0.5262	0.6365	0.7978
0.0927	63.0	126	0.6308	0.5254	0.6310	0.7944
0.0927	64.0	128	0.6435	0.5093	0.6438	0.8023
0.0848	65.0	130	0.6757	0.4915	0.6760	0.8222
0.0848	66.0	132	0.6815	0.4786	0.6818	0.8257
0.0848	67.0	134	0.6789	0.4796	0.6792	0.8241
0.0848	68.0	136	0.7008	0.4735	0.7011	0.8373
0.0848	69.0	138	0.6609	0.4744	0.6612	0.8132
0.0749	70.0	140	0.6589	0.4833	0.6592	0.8119
0.0749	71.0	142	0.7005	0.4698	0.7008	0.8371
0.0749	72.0	144	0.6741	0.4691	0.6743	0.8212
0.0749	73.0	146	0.6378	0.4769	0.6380	0.7988
0.0749	74.0	148	0.6531	0.4702	0.6534	0.8083
0.0608	75.0	150	0.7219	0.4662	0.7221	0.8498
0.0608	76.0	152	0.6908	0.4861	0.6911	0.8313
0.0608	77.0	154	0.6391	0.4739	0.6394	0.7996
0.0608	78.0	156	0.6611	0.4489	0.6613	0.8132
0.0608	79.0	158	0.6871	0.4653	0.6874	0.8291
0.0703	80.0	160	0.6719	0.4661	0.6722	0.8199
0.0703	81.0	162	0.6486	0.4885	0.6489	0.8055
0.0703	82.0	164	0.6383	0.4938	0.6385	0.7991
0.0703	83.0	166	0.6399	0.5085	0.6402	0.8001
0.0703	84.0	168	0.6547	0.5113	0.6549	0.8093
0.0626	85.0	170	0.6431	0.5137	0.6433	0.8021
0.0626	86.0	172	0.6311	0.5123	0.6313	0.7945
0.0626	87.0	174	0.6235	0.5129	0.6237	0.7898
0.0626	88.0	176	0.6175	0.5083	0.6177	0.7859
0.0626	89.0	178	0.6279	0.4901	0.6281	0.7925
0.0586	90.0	180	0.6535	0.4879	0.6537	0.8085
0.0586	91.0	182	0.6582	0.4885	0.6584	0.8114
0.0586	92.0	184	0.6614	0.4881	0.6616	0.8134
0.0586	93.0	186	0.6539	0.4818	0.6541	0.8088
0.0586	94.0	188	0.6578	0.4818	0.6580	0.8112
0.0554	95.0	190	0.6562	0.4762	0.6564	0.8102
0.0554	96.0	192	0.6470	0.4885	0.6472	0.8045
0.0554	97.0	194	0.6403	0.4846	0.6406	0.8003
0.0554	98.0	196	0.6404	0.4842	0.6406	0.8004
0.0554	99.0	198	0.6424	0.4876	0.6426	0.8016
0.0526	100.0	200	0.6430	0.4876	0.6433	0.8020

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

genki10/ASAP_FineTuningBERT_AugV6_k2_task1_organization_fold2

ASAP_FineTuningBERT_AugV6_k2_task1_organization_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k2_task1_organization_fold2