Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	11.8189	-0.0234	11.8178	3.4377
No log	2.0	4	9.3777	0.0	9.3769	3.0622
No log	3.0	6	7.4996	0.0	7.4990	2.7384
No log	4.0	8	6.2128	0.0088	6.2124	2.4925
6.9522	5.0	10	4.7513	0.0114	4.7511	2.1797
6.9522	6.0	12	3.6727	0.0038	3.6728	1.9165
6.9522	7.0	14	2.9617	0.0	2.9618	1.7210
6.9522	8.0	16	2.2386	0.1109	2.2389	1.4963
6.9522	9.0	18	1.7999	0.0365	1.8004	1.3418
2.657	10.0	20	1.4383	0.0302	1.4389	1.1995
2.657	11.0	22	1.3553	0.0202	1.3559	1.1644
2.657	12.0	24	1.1615	0.0202	1.1622	1.0781
2.657	13.0	26	1.1866	0.0365	1.1873	1.0896
2.657	14.0	28	1.0400	0.0365	1.0406	1.0201
1.8814	15.0	30	1.2076	0.0238	1.2082	1.0992
1.8814	16.0	32	0.8879	0.2366	0.8885	0.9426
1.8814	17.0	34	0.7773	0.4180	0.7777	0.8819
1.8814	18.0	36	0.7342	0.4002	0.7346	0.8571
1.8814	19.0	38	0.6936	0.4544	0.6939	0.8330
1.5961	20.0	40	0.7029	0.4765	0.7032	0.8386
1.5961	21.0	42	0.6835	0.5045	0.6837	0.8269
1.5961	22.0	44	0.6004	0.5228	0.6005	0.7749
1.5961	23.0	46	0.5569	0.5163	0.5571	0.7464
1.5961	24.0	48	0.5619	0.5455	0.5621	0.7497
1.0283	25.0	50	0.5267	0.5160	0.5268	0.7258
1.0283	26.0	52	0.5166	0.5221	0.5167	0.7188
1.0283	27.0	54	0.5102	0.5140	0.5103	0.7144
1.0283	28.0	56	0.5385	0.5116	0.5386	0.7339
1.0283	29.0	58	0.4967	0.5678	0.4967	0.7047
0.6249	30.0	60	0.4969	0.5701	0.4968	0.7049
0.6249	31.0	62	0.5434	0.5974	0.5433	0.7371
0.6249	32.0	64	0.6114	0.5480	0.6112	0.7818
0.6249	33.0	66	0.5000	0.6406	0.4999	0.7071
0.6249	34.0	68	0.5784	0.5528	0.5783	0.7604
0.796	35.0	70	0.6569	0.5218	0.6568	0.8104
0.796	36.0	72	0.6251	0.5508	0.6250	0.7905
0.796	37.0	74	0.6149	0.5585	0.6148	0.7841
0.796	38.0	76	0.5270	0.6096	0.5269	0.7259
0.796	39.0	78	0.5199	0.6441	0.5197	0.7209
0.5781	40.0	80	0.5313	0.6411	0.5311	0.7288
0.5781	41.0	82	0.5272	0.6531	0.5271	0.7260
0.5781	42.0	84	0.5289	0.6099	0.5287	0.7271
0.5781	43.0	86	0.5549	0.6038	0.5547	0.7448
0.5781	44.0	88	0.5316	0.6211	0.5313	0.7289
0.2692	45.0	90	0.5426	0.6644	0.5423	0.7364
0.2692	46.0	92	0.5980	0.6204	0.5976	0.7731
0.2692	47.0	94	0.6082	0.6128	0.6079	0.7797
0.2692	48.0	96	0.5646	0.6400	0.5642	0.7511
0.2692	49.0	98	0.5172	0.6467	0.5168	0.7189
0.2283	50.0	100	0.5440	0.6256	0.5437	0.7373
0.2283	51.0	102	0.5287	0.6522	0.5283	0.7268
0.2283	52.0	104	0.5919	0.6452	0.5915	0.7691
0.2283	53.0	106	0.5649	0.6700	0.5645	0.7513
0.2283	54.0	108	0.5434	0.6567	0.5430	0.7369
0.1511	55.0	110	0.5380	0.6575	0.5376	0.7332
0.1511	56.0	112	0.5391	0.6667	0.5387	0.7340
0.1511	57.0	114	0.5661	0.6521	0.5657	0.7521
0.1511	58.0	116	0.5787	0.6431	0.5783	0.7605
0.1511	59.0	118	0.5847	0.6377	0.5843	0.7644
0.1308	60.0	120	0.5956	0.6476	0.5952	0.7715
0.1308	61.0	122	0.5747	0.6549	0.5743	0.7578
0.1308	62.0	124	0.5772	0.6511	0.5768	0.7595
0.1308	63.0	126	0.5786	0.6489	0.5781	0.7603
0.1308	64.0	128	0.5708	0.6495	0.5704	0.7552
0.1027	65.0	130	0.5595	0.6607	0.5591	0.7477
0.1027	66.0	132	0.5613	0.6530	0.5609	0.7489
0.1027	67.0	134	0.5499	0.6560	0.5495	0.7413
0.1027	68.0	136	0.5577	0.6562	0.5573	0.7465
0.1027	69.0	138	0.5713	0.6560	0.5708	0.7555
0.1097	70.0	140	0.5963	0.6509	0.5958	0.7719
0.1097	71.0	142	0.5958	0.6481	0.5953	0.7715
0.1097	72.0	144	0.5794	0.6510	0.5789	0.7608
0.1097	73.0	146	0.5702	0.6543	0.5697	0.7548
0.1097	74.0	148	0.5650	0.6469	0.5645	0.7513
0.0794	75.0	150	0.5803	0.6518	0.5798	0.7614
0.0794	76.0	152	0.6593	0.6260	0.6587	0.8116
0.0794	77.0	154	0.6472	0.6430	0.6467	0.8041
0.0794	78.0	156	0.6105	0.6448	0.6099	0.7810
0.0794	79.0	158	0.5826	0.6398	0.5820	0.7629
0.0775	80.0	160	0.5801	0.6409	0.5796	0.7613
0.0775	81.0	162	0.5881	0.6388	0.5875	0.7665
0.0775	82.0	164	0.6314	0.6400	0.6308	0.7943
0.0775	83.0	166	0.6654	0.6288	0.6648	0.8153
0.0775	84.0	168	0.6705	0.6272	0.6699	0.8185
0.0867	85.0	170	0.6543	0.6374	0.6537	0.8085
0.0867	86.0	172	0.6428	0.6383	0.6422	0.8014
0.0867	87.0	174	0.6012	0.6464	0.6007	0.7750
0.0867	88.0	176	0.5805	0.6391	0.5800	0.7615
0.0867	89.0	178	0.5736	0.6436	0.5731	0.7570
0.0664	90.0	180	0.5719	0.6462	0.5714	0.7559
0.0664	91.0	182	0.5751	0.6467	0.5746	0.7580
0.0664	92.0	184	0.5856	0.6386	0.5851	0.7649
0.0664	93.0	186	0.6057	0.6516	0.6052	0.7779
0.0664	94.0	188	0.6204	0.6441	0.6198	0.7873
0.0657	95.0	190	0.6297	0.6404	0.6292	0.7932
0.0657	96.0	192	0.6236	0.6441	0.6231	0.7893
0.0657	97.0	194	0.6173	0.6485	0.6167	0.7853
0.0657	98.0	196	0.6148	0.6542	0.6143	0.7838
0.0657	99.0	198	0.6110	0.6570	0.6104	0.7813
0.0654	100.0	200	0.6093	0.6570	0.6088	0.7803

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_fold3

ASAP_FineTuningBERT_AugV6_k2_task1_organization_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k2_task1_organization_fold3