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	3	6.9710	0.0	6.9714	2.6403
No log	2.0	6	4.5116	0.0050	4.5121	2.1242
No log	3.0	9	3.3597	0.0	3.3600	1.8330
No log	4.0	12	2.3923	0.0737	2.3926	1.5468
No log	5.0	15	1.6913	0.0107	1.6918	1.3007
No log	6.0	18	1.2723	0.0	1.2728	1.1282
No log	7.0	21	0.9798	0.0	0.9803	0.9901
No log	8.0	24	0.8475	0.0840	0.8480	0.9209
No log	9.0	27	0.8440	0.0164	0.8445	0.9190
No log	10.0	30	0.9096	0.0164	0.9100	0.9539
No log	11.0	33	1.2171	0.0	1.2176	1.1035
No log	12.0	36	1.3437	0.1926	1.3438	1.1592
No log	13.0	39	1.6714	0.1148	1.6713	1.2928
No log	14.0	42	1.5905	0.2201	1.5898	1.2609
No log	15.0	45	0.7798	0.5548	0.7787	0.8825
No log	16.0	48	1.2070	0.4827	1.2056	1.0980
No log	17.0	51	1.0974	0.5282	1.0958	1.0468
No log	18.0	54	0.8095	0.5330	0.8090	0.8994
No log	19.0	57	0.7875	0.5329	0.7864	0.8868
No log	20.0	60	0.5547	0.5635	0.5542	0.7444
No log	21.0	63	0.6065	0.5917	0.6059	0.7784
No log	22.0	66	0.6134	0.6183	0.6130	0.7829
No log	23.0	69	0.9788	0.5429	0.9778	0.9888
No log	24.0	72	1.1164	0.5076	1.1153	1.0561
No log	25.0	75	0.5787	0.5819	0.5785	0.7606
No log	26.0	78	1.4170	0.3433	1.4164	1.1901
No log	27.0	81	1.1652	0.3876	1.1647	1.0792
No log	28.0	84	0.6935	0.5254	0.6933	0.8327
No log	29.0	87	0.8046	0.4981	0.8042	0.8967
No log	30.0	90	0.6635	0.5231	0.6637	0.8147
No log	31.0	93	0.5800	0.5609	0.5800	0.7616
No log	32.0	96	1.4863	0.4027	1.4851	1.2187
No log	33.0	99	2.0766	0.3156	2.0752	1.4405
No log	34.0	102	0.8286	0.5471	0.8278	0.9098
No log	35.0	105	0.6546	0.6002	0.6540	0.8087
No log	36.0	108	1.0056	0.5189	1.0045	1.0022
No log	37.0	111	0.6342	0.6001	0.6338	0.7961
No log	38.0	114	0.5762	0.5735	0.5763	0.7591
No log	39.0	117	0.6253	0.5744	0.6249	0.7905
No log	40.0	120	0.6284	0.5783	0.6280	0.7925
No log	41.0	123	0.5893	0.5931	0.5890	0.7675
No log	42.0	126	1.0307	0.4540	1.0297	1.0147

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2

Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2