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	9.7287	0.0018	9.7287	3.1191
No log	2.0	6	8.4098	0.0	8.4098	2.9000
No log	3.0	9	6.7081	0.0	6.7081	2.5900
No log	4.0	12	4.5510	0.0079	4.5510	2.1333
No log	5.0	15	3.3840	0.0040	3.3840	1.8396
No log	6.0	18	2.5402	0.0040	2.5402	1.5938
No log	7.0	21	1.7890	0.0547	1.7890	1.3375
No log	8.0	24	1.3439	0.0239	1.3439	1.1593
No log	9.0	27	1.0291	0.0798	1.0291	1.0144
No log	10.0	30	0.7933	0.3966	0.7933	0.8907
No log	11.0	33	0.6911	0.5375	0.6911	0.8313
No log	12.0	36	0.6277	0.5470	0.6277	0.7923
No log	13.0	39	1.2072	0.3868	1.2072	1.0987
No log	14.0	42	0.7456	0.5210	0.7456	0.8635
No log	15.0	45	0.5702	0.5499	0.5702	0.7551
No log	16.0	48	0.7661	0.4456	0.7661	0.8753
No log	17.0	51	0.6000	0.4861	0.6000	0.7746
No log	18.0	54	0.8547	0.4875	0.8547	0.9245
No log	19.0	57	0.5640	0.5518	0.5640	0.7510
No log	20.0	60	0.6778	0.4298	0.6778	0.8233
No log	21.0	63	0.5484	0.5565	0.5484	0.7406
No log	22.0	66	0.7987	0.4728	0.7987	0.8937
No log	23.0	69	0.6607	0.5658	0.6607	0.8129
No log	24.0	72	0.6020	0.5801	0.6020	0.7759
No log	25.0	75	0.6551	0.5685	0.6551	0.8094
No log	26.0	78	0.6946	0.5852	0.6946	0.8334
No log	27.0	81	0.6481	0.6283	0.6481	0.8050
No log	28.0	84	0.8342	0.5911	0.8342	0.9134
No log	29.0	87	0.7286	0.6177	0.7286	0.8536
No log	30.0	90	0.5790	0.6023	0.5790	0.7609
No log	31.0	93	0.5888	0.5795	0.5888	0.7673
No log	32.0	96	0.7320	0.5808	0.7320	0.8556
No log	33.0	99	0.6128	0.6176	0.6128	0.7828
No log	34.0	102	0.6234	0.5974	0.6234	0.7896
No log	35.0	105	0.5608	0.6219	0.5608	0.7489
No log	36.0	108	0.6216	0.6004	0.6216	0.7884
No log	37.0	111	0.6977	0.5988	0.6977	0.8353
No log	38.0	114	0.6989	0.5979	0.6989	0.8360
No log	39.0	117	0.5859	0.6109	0.5859	0.7654
No log	40.0	120	0.6080	0.5797	0.6080	0.7797
No log	41.0	123	0.5705	0.6262	0.5705	0.7553
No log	42.0	126	0.6452	0.6080	0.6452	0.8033
No log	43.0	129	0.6470	0.6142	0.6470	0.8044
No log	44.0	132	0.7422	0.5798	0.7422	0.8615
No log	45.0	135	0.5954	0.6119	0.5954	0.7716
No log	46.0	138	0.6140	0.5892	0.6140	0.7836
No log	47.0	141	0.5670	0.6196	0.5670	0.7530

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold4

ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold4