learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	6	5.2716	0.0344	5.2704	2.2957
No log	2.0	12	2.4981	0.1149	2.4973	1.5803
No log	3.0	18	1.3630	0.0266	1.3623	1.1672
No log	4.0	24	2.1347	0.0130	2.1334	1.4606
No log	5.0	30	1.1351	0.0391	1.1347	1.0652
No log	6.0	36	0.9583	0.1629	0.9580	0.9788
No log	7.0	42	0.8432	0.2155	0.8429	0.9181
No log	8.0	48	0.8334	0.1743	0.8333	0.9128
No log	9.0	54	1.2599	-0.0385	1.2594	1.1222
No log	10.0	60	0.9813	0.1109	0.9815	0.9907
No log	11.0	66	0.9961	0.1710	0.9962	0.9981
No log	12.0	72	0.9674	0.3145	0.9677	0.9837
No log	13.0	78	0.7973	0.3534	0.7976	0.8931
No log	14.0	84	0.9710	0.3304	0.9715	0.9857
No log	15.0	90	0.9817	0.3464	0.9821	0.9910
No log	16.0	96	0.8926	0.3733	0.8931	0.9450
No log	17.0	102	0.9888	0.2958	0.9892	0.9946
No log	18.0	108	1.4593	-0.0255	1.4592	1.2080
No log	19.0	114	1.1688	0.3036	1.1696	1.0815
No log	20.0	120	1.0462	0.2992	1.0469	1.0232
No log	21.0	126	1.1312	0.3513	1.1320	1.0640
No log	22.0	132	1.1308	0.1441	1.1313	1.0636
No log	23.0	138	1.0583	0.3702	1.0590	1.0291
No log	24.0	144	1.0179	0.2525	1.0183	1.0091
No log	25.0	150	1.1938	0.2891	1.1946	1.0930
No log	26.0	156	1.1304	0.1981	1.1307	1.0633
No log	27.0	162	1.0898	0.2843	1.0905	1.0443
No log	28.0	168	0.9583	0.2642	0.9587	0.9791
No log	29.0	174	1.2991	0.1550	1.2998	1.1401
No log	30.0	180	1.3082	0.0706	1.3086	1.1439
No log	31.0	186	1.2172	0.3761	1.2178	1.1035
No log	32.0	192	1.1213	0.1473	1.1213	1.0589
No log	33.0	198	1.1034	0.1809	1.1038	1.0506
No log	34.0	204	1.1515	0.2966	1.1521	1.0734
No log	35.0	210	1.1995	0.1297	1.1998	1.0954
No log	36.0	216	1.1732	0.1576	1.1735	1.0833
No log	37.0	222	1.0714	0.2106	1.0715	1.0351
No log	38.0	228	0.9837	0.2932	0.9842	0.9921
No log	39.0	234	1.1448	0.2459	1.1454	1.0702
No log	40.0	240	1.0027	0.3056	1.0032	1.0016
No log	41.0	246	1.0796	0.3289	1.0804	1.0394
No log	42.0	252	1.2787	0.1194	1.2794	1.1311
No log	43.0	258	1.3468	0.0837	1.3474	1.1608
No log	44.0	264	1.1938	0.2431	1.1946	1.0930
No log	45.0	270	1.1135	0.2948	1.1143	1.0556
No log	46.0	276	1.1977	0.1029	1.1981	1.0946
No log	47.0	282	1.2110	0.1323	1.2115	1.1007
No log	48.0	288	1.0055	0.2853	1.0061	1.0030
No log	49.0	294	1.0380	0.2801	1.0385	1.0191
No log	50.0	300	1.1552	0.2188	1.1558	1.0751
No log	51.0	306	1.2341	0.1067	1.2346	1.1111

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold3

Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold3