Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	10.9197	-0.0118	10.9197	3.3045
No log	2.0	4	8.7217	0.0018	8.7217	2.9532
No log	3.0	6	6.9431	0.0018	6.9431	2.6350
No log	4.0	8	5.8731	0.0053	5.8731	2.4234
6.8101	5.0	10	4.4105	0.0118	4.4105	2.1001
6.8101	6.0	12	3.5593	0.0040	3.5593	1.8866
6.8101	7.0	14	2.9146	0.0040	2.9146	1.7072
6.8101	8.0	16	2.2145	0.1767	2.2145	1.4881
6.8101	9.0	18	1.7794	0.0445	1.7794	1.3339
3.317	10.0	20	1.4552	0.0420	1.4552	1.2063
3.317	11.0	22	1.2147	0.0420	1.2147	1.1021
3.317	12.0	24	1.0919	0.0420	1.0919	1.0450
3.317	13.0	26	0.9082	0.0522	0.9082	0.9530
3.317	14.0	28	0.8389	0.1370	0.8389	0.9159
1.9504	15.0	30	1.0749	0.1440	1.0749	1.0368
1.9504	16.0	32	0.9480	0.2112	0.9480	0.9737
1.9504	17.0	34	0.7247	0.4525	0.7247	0.8513
1.9504	18.0	36	0.7789	0.4409	0.7789	0.8825
1.9504	19.0	38	0.8688	0.4017	0.8688	0.9321
1.5746	20.0	40	0.7049	0.5069	0.7049	0.8396
1.5746	21.0	42	0.6353	0.5255	0.6353	0.7970
1.5746	22.0	44	0.6329	0.5304	0.6329	0.7955
1.5746	23.0	46	0.5916	0.5152	0.5916	0.7692
1.5746	24.0	48	0.5696	0.5138	0.5696	0.7547
0.925	25.0	50	0.5646	0.5249	0.5646	0.7514
0.925	26.0	52	0.6559	0.5335	0.6559	0.8099
0.925	27.0	54	0.6281	0.4877	0.6281	0.7925
0.925	28.0	56	0.6637	0.4699	0.6637	0.8147
0.925	29.0	58	0.6711	0.4913	0.6711	0.8192
0.4965	30.0	60	0.6141	0.5557	0.6141	0.7836
0.4965	31.0	62	0.6267	0.6059	0.6267	0.7917
0.4965	32.0	64	0.6265	0.5689	0.6265	0.7915
0.4965	33.0	66	0.6299	0.5440	0.6299	0.7936
0.4965	34.0	68	0.7134	0.5355	0.7134	0.8446
0.321	35.0	70	0.7295	0.5334	0.7295	0.8541
0.321	36.0	72	0.7219	0.5415	0.7219	0.8496
0.321	37.0	74	0.6519	0.5613	0.6519	0.8074
0.321	38.0	76	0.6641	0.5455	0.6641	0.8150
0.321	39.0	78	0.6316	0.5695	0.6316	0.7948
0.1961	40.0	80	0.6552	0.5930	0.6552	0.8094
0.1961	41.0	82	0.6228	0.5764	0.6228	0.7891
0.1961	42.0	84	0.6784	0.5570	0.6784	0.8237
0.1961	43.0	86	0.6439	0.5647	0.6439	0.8025
0.1961	44.0	88	0.7116	0.5621	0.7116	0.8436
0.1482	45.0	90	0.6760	0.5807	0.6760	0.8222
0.1482	46.0	92	0.6715	0.5911	0.6715	0.8194
0.1482	47.0	94	0.5897	0.5708	0.5897	0.7679
0.1482	48.0	96	0.5838	0.5639	0.5838	0.7641
0.1482	49.0	98	0.6033	0.5712	0.6033	0.7767
0.1251	50.0	100	0.5836	0.5611	0.5836	0.7639
0.1251	51.0	102	0.5841	0.5744	0.5841	0.7643
0.1251	52.0	104	0.6658	0.5947	0.6658	0.8160
0.1251	53.0	106	0.6178	0.6214	0.6178	0.7860
0.1251	54.0	108	0.6131	0.6248	0.6131	0.7830
0.1173	55.0	110	0.6709	0.6275	0.6709	0.8191
0.1173	56.0	112	0.6357	0.6247	0.6357	0.7973
0.1173	57.0	114	0.6134	0.6078	0.6134	0.7832
0.1173	58.0	116	0.7196	0.5862	0.7196	0.8483
0.1173	59.0	118	0.7126	0.5890	0.7126	0.8442
0.1091	60.0	120	0.5951	0.5804	0.5951	0.7714
0.1091	61.0	122	0.5996	0.5710	0.5996	0.7743
0.1091	62.0	124	0.6186	0.5715	0.6186	0.7865
0.1091	63.0	126	0.7158	0.5905	0.7158	0.8461
0.1091	64.0	128	0.6546	0.5687	0.6546	0.8090
0.1051	65.0	130	0.5840	0.5796	0.5840	0.7642
0.1051	66.0	132	0.5749	0.5837	0.5749	0.7582
0.1051	67.0	134	0.6063	0.5978	0.6063	0.7786
0.1051	68.0	136	0.6289	0.6193	0.6289	0.7930
0.1051	69.0	138	0.6280	0.6216	0.6280	0.7924
0.0956	70.0	140	0.5852	0.6072	0.5852	0.7650
0.0956	71.0	142	0.5998	0.6054	0.5998	0.7745
0.0956	72.0	144	0.6888	0.6075	0.6888	0.8299
0.0956	73.0	146	0.7301	0.6041	0.7301	0.8545
0.0956	74.0	148	0.6466	0.6101	0.6466	0.8041
0.075	75.0	150	0.6202	0.6157	0.6202	0.7876
0.075	76.0	152	0.6237	0.6067	0.6237	0.7897
0.075	77.0	154	0.6541	0.5900	0.6541	0.8088
0.075	78.0	156	0.6324	0.6016	0.6324	0.7952
0.075	79.0	158	0.6074	0.5968	0.6074	0.7794
0.0541	80.0	160	0.5953	0.6039	0.5953	0.7716
0.0541	81.0	162	0.5934	0.6060	0.5934	0.7703
0.0541	82.0	164	0.6124	0.6160	0.6124	0.7826
0.0541	83.0	166	0.6307	0.6032	0.6307	0.7942
0.0541	84.0	168	0.6283	0.6038	0.6283	0.7927
0.0564	85.0	170	0.6119	0.5978	0.6119	0.7822
0.0564	86.0	172	0.6203	0.5992	0.6203	0.7876
0.0564	87.0	174	0.6678	0.5978	0.6678	0.8172
0.0564	88.0	176	0.6933	0.6043	0.6933	0.8327
0.0564	89.0	178	0.6749	0.6002	0.6749	0.8216
0.0513	90.0	180	0.6350	0.6000	0.6350	0.7968
0.0513	91.0	182	0.6211	0.6068	0.6211	0.7881
0.0513	92.0	184	0.6206	0.6068	0.6206	0.7878
0.0513	93.0	186	0.6315	0.5955	0.6315	0.7947
0.0513	94.0	188	0.6582	0.6076	0.6582	0.8113
0.0663	95.0	190	0.6926	0.5995	0.6926	0.8322
0.0663	96.0	192	0.7021	0.6146	0.7021	0.8379
0.0663	97.0	194	0.6959	0.6065	0.6959	0.8342
0.0663	98.0	196	0.6885	0.6081	0.6885	0.8298
0.0663	99.0	198	0.6828	0.6031	0.6828	0.8263
0.052	100.0	200	0.6795	0.5971	0.6795	0.8243

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

genki10/ASAP_FineTuningBERT_AugV6_k1_task1_organization_fold4

ASAP_FineTuningBERT_AugV6_k1_task1_organization_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k1_task1_organization_fold4