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	12.0717	0.0009	12.0698	3.4742
No log	2.0	6	9.4695	0.0	9.4677	3.0770
No log	3.0	9	6.1376	0.0415	6.1366	2.4772
No log	4.0	12	5.3414	0.0008	5.3399	2.3108
No log	5.0	15	3.2498	0.0	3.2489	1.8025
No log	6.0	18	2.1548	0.1777	2.1541	1.4677
No log	7.0	21	1.6038	0.0302	1.6032	1.2662
No log	8.0	24	1.0416	0.0	1.0412	1.0204
No log	9.0	27	0.8096	0.3611	0.8094	0.8997
No log	10.0	30	0.7585	0.2121	0.7584	0.8708
No log	11.0	33	0.7816	0.0965	0.7815	0.8840
No log	12.0	36	1.0720	0.0761	1.0722	1.0354
No log	13.0	39	1.2815	0.2235	1.2817	1.1321
No log	14.0	42	0.9776	0.2553	0.9774	0.9886
No log	15.0	45	1.5095	0.2405	1.5094	1.2286
No log	16.0	48	1.5545	0.2484	1.5544	1.2468
No log	17.0	51	0.9760	0.3735	0.9756	0.9877
No log	18.0	54	1.1234	0.3976	1.1228	1.0596
No log	19.0	57	0.7982	0.5433	0.7976	0.8931
No log	20.0	60	0.9736	0.5053	0.9730	0.9864
No log	21.0	63	1.2969	0.4917	1.2962	1.1385
No log	22.0	66	1.4159	0.4577	1.4156	1.1898
No log	23.0	69	0.9062	0.5893	0.9060	0.9518
No log	24.0	72	0.8942	0.5854	0.8936	0.9453
No log	25.0	75	0.6068	0.6712	0.6065	0.7788
No log	26.0	78	0.7226	0.6419	0.7222	0.8498
No log	27.0	81	0.6705	0.6387	0.6702	0.8187
No log	28.0	84	0.9323	0.6028	0.9316	0.9652
No log	29.0	87	0.7179	0.6613	0.7174	0.8470
No log	30.0	90	0.7261	0.6553	0.7256	0.8518
No log	31.0	93	0.8450	0.6220	0.8444	0.9189
No log	32.0	96	0.6194	0.6677	0.6190	0.7868
No log	33.0	99	0.9931	0.5840	0.9922	0.9961
No log	34.0	102	1.0582	0.5728	1.0572	1.0282
No log	35.0	105	0.6230	0.6405	0.6225	0.7890
No log	36.0	108	0.6099	0.6349	0.6094	0.7807
No log	37.0	111	0.6919	0.6572	0.6912	0.8314
No log	38.0	114	0.5996	0.6637	0.5990	0.7740
No log	39.0	117	0.7404	0.6403	0.7396	0.8600
No log	40.0	120	0.7253	0.6343	0.7247	0.8513
No log	41.0	123	0.7309	0.6434	0.7302	0.8545
No log	42.0	126	0.6923	0.6358	0.6917	0.8317
No log	43.0	129	0.8151	0.6079	0.8142	0.9023
No log	44.0	132	0.6924	0.6362	0.6917	0.8317
No log	45.0	135	0.7067	0.6518	0.7060	0.8403

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3

ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3