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	5.4152	0.0189	5.4155	2.3271
No log	2.0	12	2.6013	0.0089	2.6018	1.6130
No log	3.0	18	1.4322	0.0	1.4327	1.1970
No log	4.0	24	1.1228	0.0	1.1232	1.0598
No log	5.0	30	1.1060	0.0	1.1063	1.0518
No log	6.0	36	1.5328	0.0787	1.5329	1.2381
No log	7.0	42	1.2487	0.1192	1.2484	1.1173
No log	8.0	48	1.1898	0.1705	1.1897	1.0907
No log	9.0	54	1.7567	0.1115	1.7562	1.3252
No log	10.0	60	0.9120	0.3181	0.9119	0.9549
No log	11.0	66	0.8388	0.3320	0.8387	0.9158
No log	12.0	72	1.6031	0.1400	1.6027	1.2660
No log	13.0	78	0.7045	0.3561	0.7047	0.8394
No log	14.0	84	1.7995	0.1357	1.7990	1.3413
No log	15.0	90	0.6219	0.3878	0.6221	0.7887
No log	16.0	96	0.9396	0.3062	0.9396	0.9693
No log	17.0	102	0.5544	0.4813	0.5543	0.7445
No log	18.0	108	0.5453	0.4707	0.5452	0.7384
No log	19.0	114	0.5760	0.5215	0.5756	0.7587
No log	20.0	120	0.5320	0.5626	0.5315	0.7290
No log	21.0	126	0.6158	0.5791	0.6153	0.7844
No log	22.0	132	0.6357	0.5773	0.6353	0.7970
No log	23.0	138	0.6928	0.5575	0.6923	0.8321
No log	24.0	144	0.8636	0.4915	0.8628	0.9289
No log	25.0	150	0.4864	0.6344	0.4861	0.6972
No log	26.0	156	0.6208	0.5497	0.6207	0.7879
No log	27.0	162	0.5834	0.5707	0.5830	0.7636
No log	28.0	168	0.7426	0.5259	0.7425	0.8617
No log	29.0	174	0.5270	0.5830	0.5268	0.7258
No log	30.0	180	0.5684	0.6009	0.5681	0.7537
No log	31.0	186	0.7277	0.5522	0.7275	0.8529
No log	32.0	192	0.5342	0.6215	0.5339	0.7307
No log	33.0	198	0.6272	0.5936	0.6269	0.7918
No log	34.0	204	0.6038	0.5998	0.6034	0.7768
No log	35.0	210	0.6144	0.5917	0.6138	0.7835
No log	36.0	216	0.5510	0.6152	0.5506	0.7420
No log	37.0	222	0.6192	0.5869	0.6189	0.7867
No log	38.0	228	0.5989	0.5833	0.5986	0.7737
No log	39.0	234	0.5552	0.5691	0.5549	0.7449
No log	40.0	240	0.7807	0.5091	0.7804	0.8834
No log	41.0	246	0.6862	0.5365	0.6858	0.8281
No log	42.0	252	0.7161	0.5563	0.7156	0.8459
No log	43.0	258	0.6970	0.5648	0.6964	0.8345
No log	44.0	264	0.6440	0.6089	0.6435	0.8022
No log	45.0	270	0.6587	0.5705	0.6583	0.8113

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_fold2

Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold2

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_fold2