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	10.0437	0.0018	10.0437	3.1692
No log	2.0	6	7.7539	0.0	7.7539	2.7846
No log	3.0	9	5.5199	0.0478	5.5199	2.3494
No log	4.0	12	4.0979	0.0040	4.0979	2.0243
No log	5.0	15	2.8818	0.0040	2.8818	1.6976
No log	6.0	18	1.9700	0.0421	1.9700	1.4036
No log	7.0	21	1.4218	0.0107	1.4218	1.1924
No log	8.0	24	1.1358	0.0107	1.1358	1.0657
No log	9.0	27	1.0761	0.0107	1.0761	1.0374
No log	10.0	30	1.3625	0.0470	1.3625	1.1673
No log	11.0	33	0.8469	0.2517	0.8469	0.9203
No log	12.0	36	0.9684	0.2029	0.9684	0.9841
No log	13.0	39	0.7850	0.3837	0.7850	0.8860
No log	14.0	42	0.7755	0.4099	0.7755	0.8806
No log	15.0	45	0.7142	0.4524	0.7142	0.8451
No log	16.0	48	0.7351	0.4353	0.7351	0.8574
No log	17.0	51	0.8130	0.4362	0.8130	0.9017
No log	18.0	54	0.7484	0.4631	0.7484	0.8651
No log	19.0	57	0.8107	0.5118	0.8107	0.9004
No log	20.0	60	0.8008	0.5056	0.8008	0.8949
No log	21.0	63	0.8279	0.5131	0.8279	0.9099
No log	22.0	66	0.8778	0.5110	0.8778	0.9369
No log	23.0	69	0.9076	0.4855	0.9076	0.9527
No log	24.0	72	0.9220	0.4985	0.9220	0.9602
No log	25.0	75	0.8977	0.5010	0.8977	0.9474
No log	26.0	78	0.9246	0.5028	0.9246	0.9616
No log	27.0	81	0.8143	0.5193	0.8143	0.9024
No log	28.0	84	0.7812	0.5503	0.7812	0.8839
No log	29.0	87	0.8928	0.5346	0.8928	0.9449
No log	30.0	90	0.8749	0.5243	0.8749	0.9353
No log	31.0	93	1.0277	0.5134	1.0277	1.0138
No log	32.0	96	0.9704	0.5563	0.9704	0.9851
No log	33.0	99	0.9424	0.5256	0.9424	0.9708
No log	34.0	102	1.2459	0.4791	1.2459	1.1162
No log	35.0	105	1.2512	0.4641	1.2512	1.1186
No log	36.0	108	0.8489	0.5137	0.8489	0.9214
No log	37.0	111	0.8584	0.5260	0.8584	0.9265
No log	38.0	114	1.3666	0.4465	1.3666	1.1690
No log	39.0	117	0.8705	0.5206	0.8705	0.9330
No log	40.0	120	0.9222	0.5293	0.9222	0.9603
No log	41.0	123	1.0273	0.5068	1.0273	1.0135
No log	42.0	126	0.8223	0.5365	0.8223	0.9068
No log	43.0	129	0.9016	0.5331	0.9016	0.9495
No log	44.0	132	0.9550	0.5079	0.9550	0.9773
No log	45.0	135	0.8975	0.5372	0.8975	0.9474
No log	46.0	138	1.2944	0.4852	1.2944	1.1377
No log	47.0	141	0.9582	0.5397	0.9582	0.9789
No log	48.0	144	1.0142	0.5279	1.0142	1.0071
No log	49.0	147	1.2131	0.4842	1.2131	1.1014
No log	50.0	150	0.8405	0.5457	0.8405	0.9168
No log	51.0	153	0.8455	0.5411	0.8455	0.9195
No log	52.0	156	1.1282	0.4829	1.1282	1.0622

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold4

ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold4