Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	11.7206	-0.0255	11.7202	3.4235
No log	2.0	4	9.4701	0.0	9.4698	3.0773
No log	3.0	6	7.5935	0.0	7.5932	2.7556
No log	4.0	8	6.1459	0.0029	6.1456	2.4790
7.1713	5.0	10	4.8213	0.0064	4.8211	2.1957
7.1713	6.0	12	3.7801	0.0	3.7799	1.9442
7.1713	7.0	14	2.8847	0.0	2.8847	1.6984
7.1713	8.0	16	2.2255	0.1236	2.2255	1.4918
7.1713	9.0	18	1.7728	0.0213	1.7729	1.3315
2.7926	10.0	20	1.4231	0.0107	1.4232	1.1930
2.7926	11.0	22	1.1937	0.0	1.1940	1.0927
2.7926	12.0	24	1.1194	0.0174	1.1195	1.0581
2.7926	13.0	26	1.0118	0.0345	1.0119	1.0059
2.7926	14.0	28	0.8565	0.1066	0.8567	0.9256
1.8235	15.0	30	0.8628	0.1304	0.8631	0.9290
1.8235	16.0	32	0.8085	0.2815	0.8087	0.8993
1.8235	17.0	34	0.9646	0.2564	0.9648	0.9822
1.8235	18.0	36	0.7329	0.4466	0.7331	0.8562
1.8235	19.0	38	0.6917	0.4197	0.6921	0.8319
1.404	20.0	40	0.7371	0.3145	0.7377	0.8589
1.404	21.0	42	0.7170	0.3193	0.7175	0.8471
1.404	22.0	44	0.6507	0.3577	0.6513	0.8070
1.404	23.0	46	0.7068	0.3556	0.7074	0.8411
1.404	24.0	48	0.7409	0.3070	0.7415	0.8611
0.7715	25.0	50	0.7460	0.2791	0.7465	0.8640
0.7715	26.0	52	0.9012	0.3077	0.9015	0.9495
0.7715	27.0	54	0.8120	0.3029	0.8124	0.9013
0.7715	28.0	56	0.7252	0.3899	0.7256	0.8518
0.7715	29.0	58	0.8757	0.3300	0.8758	0.9359
0.3592	30.0	60	0.8814	0.3234	0.8815	0.9389
0.3592	31.0	62	0.7558	0.4216	0.7561	0.8696
0.3592	32.0	64	0.8237	0.3856	0.8241	0.9078
0.3592	33.0	66	0.8525	0.3585	0.8526	0.9234
0.3592	34.0	68	0.8942	0.3304	0.8943	0.9457
0.2724	35.0	70	0.7905	0.3911	0.7909	0.8893
0.2724	36.0	72	0.7424	0.4312	0.7428	0.8618
0.2724	37.0	74	0.7227	0.4750	0.7230	0.8503
0.2724	38.0	76	0.7324	0.4569	0.7327	0.8560
0.2724	39.0	78	0.7830	0.4114	0.7834	0.8851
0.185	40.0	80	0.8023	0.4065	0.8026	0.8959
0.185	41.0	82	0.7710	0.3766	0.7712	0.8782
0.185	42.0	84	0.7945	0.4009	0.7948	0.8915
0.185	43.0	86	0.7205	0.4169	0.7208	0.8490
0.185	44.0	88	0.7175	0.4139	0.7177	0.8472
0.1379	45.0	90	0.7200	0.4403	0.7202	0.8486
0.1379	46.0	92	0.8236	0.4342	0.8240	0.9077
0.1379	47.0	94	0.7955	0.4064	0.7958	0.8921
0.1379	48.0	96	0.7813	0.3685	0.7815	0.8841
0.1379	49.0	98	0.8098	0.4022	0.8102	0.9001
0.106	50.0	100	0.7544	0.4030	0.7547	0.8687
0.106	51.0	102	0.7788	0.3870	0.7789	0.8826
0.106	52.0	104	0.7449	0.4236	0.7452	0.8633
0.106	53.0	106	0.8246	0.4130	0.8250	0.9083
0.106	54.0	108	0.7948	0.3779	0.7952	0.8917
0.1022	55.0	110	0.7902	0.4207	0.7903	0.8890
0.1022	56.0	112	0.7786	0.4063	0.7789	0.8825
0.1022	57.0	114	0.7791	0.4307	0.7795	0.8829
0.1022	58.0	116	0.7324	0.4409	0.7328	0.8560
0.1022	59.0	118	0.6701	0.4653	0.6703	0.8187
0.1076	60.0	120	0.6794	0.4747	0.6796	0.8244
0.1076	61.0	122	0.7277	0.4350	0.7280	0.8532
0.1076	62.0	124	0.8073	0.4061	0.8076	0.8987
0.1076	63.0	126	0.7791	0.3855	0.7793	0.8828
0.1076	64.0	128	0.7705	0.3934	0.7707	0.8779
0.0761	65.0	130	0.7962	0.4133	0.7965	0.8925
0.0761	66.0	132	0.7597	0.4257	0.7600	0.8718
0.0761	67.0	134	0.6835	0.4801	0.6837	0.8269
0.0761	68.0	136	0.6809	0.4655	0.6811	0.8253
0.0761	69.0	138	0.6810	0.4717	0.6813	0.8254
0.0683	70.0	140	0.6956	0.4696	0.6958	0.8342
0.0683	71.0	142	0.7047	0.4618	0.7050	0.8396
0.0683	72.0	144	0.7038	0.4725	0.7040	0.8391
0.0683	73.0	146	0.7219	0.4397	0.7221	0.8498
0.0683	74.0	148	0.7098	0.4641	0.7100	0.8426
0.0623	75.0	150	0.7040	0.4543	0.7042	0.8392
0.0623	76.0	152	0.7075	0.4467	0.7077	0.8412
0.0623	77.0	154	0.7215	0.4279	0.7217	0.8496
0.0623	78.0	156	0.7544	0.3754	0.7547	0.8687
0.0623	79.0	158	0.7597	0.3699	0.7600	0.8718
0.0672	80.0	160	0.7439	0.4098	0.7441	0.8626
0.0672	81.0	162	0.7427	0.4032	0.7430	0.8620
0.0672	82.0	164	0.7428	0.4002	0.7431	0.8620
0.0672	83.0	166	0.7093	0.4278	0.7096	0.8424
0.0672	84.0	168	0.6788	0.4932	0.6790	0.8240
0.0605	85.0	170	0.6715	0.4921	0.6717	0.8196
0.0605	86.0	172	0.6725	0.4831	0.6727	0.8202
0.0605	87.0	174	0.6941	0.4651	0.6944	0.8333
0.0605	88.0	176	0.6983	0.4547	0.6986	0.8358
0.0605	89.0	178	0.6909	0.4418	0.6911	0.8313
0.0547	90.0	180	0.6909	0.4429	0.6912	0.8314
0.0547	91.0	182	0.6957	0.4415	0.6960	0.8343
0.0547	92.0	184	0.6996	0.4381	0.6998	0.8365
0.0547	93.0	186	0.6978	0.4415	0.6980	0.8355
0.0547	94.0	188	0.6993	0.4344	0.6995	0.8364
0.0615	95.0	190	0.7060	0.4281	0.7063	0.8404
0.0615	96.0	192	0.7109	0.4287	0.7111	0.8433
0.0615	97.0	194	0.7131	0.4287	0.7133	0.8446
0.0615	98.0	196	0.7138	0.4170	0.7140	0.8450
0.0615	99.0	198	0.7148	0.4170	0.7150	0.8456
0.0499	100.0	200	0.7151	0.4170	0.7154	0.8458

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_fold2

ASAP_FineTuningBERT_AugV7_k2_task1_organization_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV7_k2_task1_organization_fold2