Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	2.0	2	9.5459	0.0	9.5437	3.0893
No log	4.0	4	7.9017	0.0	7.8997	2.8106
No log	6.0	6	6.3366	0.0	6.3350	2.5169
No log	8.0	8	5.0299	0.0176	5.0286	2.2424
8.8038	10.0	10	4.1224	0.0040	4.1214	2.0301
8.8038	12.0	12	3.3632	0.0	3.3623	1.8337
8.8038	14.0	14	2.6701	0.0	2.6695	1.6339
8.8038	16.0	16	2.2052	0.0936	2.2049	1.4849
8.8038	18.0	18	1.8335	0.0315	1.8333	1.3540
4.3292	20.0	20	1.5592	0.0106	1.5592	1.2487
4.3292	22.0	22	1.2923	0.0315	1.2924	1.1368
4.3292	24.0	24	1.1033	0.0315	1.1033	1.0504
4.3292	26.0	26	0.9594	0.0315	0.9595	0.9795
4.3292	28.0	28	0.8174	0.2166	0.8175	0.9041
2.5258	30.0	30	0.7559	0.3569	0.7559	0.8694
2.5258	32.0	32	0.6751	0.4660	0.6751	0.8216
2.5258	34.0	34	0.5730	0.5941	0.5729	0.7569
2.5258	36.0	36	0.6422	0.4592	0.6422	0.8014
2.5258	38.0	38	0.6326	0.5062	0.6325	0.7953
1.3646	40.0	40	0.4732	0.5909	0.4730	0.6878
1.3646	42.0	42	0.5659	0.5203	0.5658	0.7522
1.3646	44.0	44	0.5829	0.5243	0.5827	0.7633
1.3646	46.0	46	0.5077	0.5890	0.5074	0.7123
1.3646	48.0	48	0.6104	0.5551	0.6100	0.7811
0.73	50.0	50	0.7074	0.4921	0.7071	0.8409
0.73	52.0	52	0.5363	0.6408	0.5359	0.7321
0.73	54.0	54	0.6001	0.5971	0.5997	0.7744
0.73	56.0	56	0.7046	0.5619	0.7041	0.8391
0.73	58.0	58	0.5219	0.6782	0.5215	0.7221
0.4451	60.0	60	0.5072	0.6768	0.5068	0.7119
0.4451	62.0	62	0.7485	0.5762	0.7480	0.8649
0.4451	64.0	64	0.7275	0.5857	0.7270	0.8526
0.4451	66.0	66	0.5534	0.6521	0.5530	0.7436
0.4451	68.0	68	0.6533	0.6090	0.6528	0.8080
0.2569	70.0	70	0.9045	0.5633	0.9038	0.9507
0.2569	72.0	72	0.8528	0.5863	0.8521	0.9231
0.2569	74.0	74	0.5916	0.6550	0.5912	0.7689
0.2569	76.0	76	0.5391	0.6595	0.5386	0.7339
0.2569	78.0	78	0.7008	0.6138	0.7003	0.8368
0.1677	80.0	80	0.9340	0.5561	0.9334	0.9661
0.1677	82.0	82	1.0176	0.5566	1.0169	1.0084
0.1677	84.0	84	0.8677	0.5885	0.8670	0.9311
0.1677	86.0	86	0.7894	0.6046	0.7888	0.8881
0.1677	88.0	88	0.8282	0.5904	0.8276	0.9097
0.1133	90.0	90	0.8855	0.5765	0.8849	0.9407
0.1133	92.0	92	0.8531	0.5751	0.8525	0.9233
0.1133	94.0	94	0.8494	0.5763	0.8488	0.9213
0.1133	96.0	96	0.8278	0.5872	0.8272	0.9095
0.1133	98.0	98	0.7835	0.5950	0.7829	0.8848
0.1027	100.0	100	0.7670	0.6013	0.7664	0.8755

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

genki10/ASAP_FineTuningBERT_UnAugV5_k1_task1_organization_fold1

ASAP_FineTuningBERT_UnAugV5_k1_task1_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_UnAugV5_k1_task1_organization_fold1