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	9.6924	0.0018	9.6924	3.1133
No log	2.0	6	8.6407	0.0	8.6407	2.9395
No log	3.0	9	6.5366	0.0	6.5366	2.5567
No log	4.0	12	4.5116	0.0079	4.5116	2.1241
No log	5.0	15	3.1358	0.0079	3.1358	1.7708
No log	6.0	18	2.2839	0.1266	2.2839	1.5112
No log	7.0	21	1.5891	0.0624	1.5891	1.2606
No log	8.0	24	1.1082	0.0316	1.1082	1.0527
No log	9.0	27	1.0564	0.0795	1.0564	1.0278
No log	10.0	30	0.9445	0.2970	0.9445	0.9719
No log	11.0	33	0.7412	0.4695	0.7412	0.8609
No log	12.0	36	0.7757	0.4818	0.7757	0.8808
No log	13.0	39	0.6332	0.4882	0.6332	0.7957
No log	14.0	42	0.6027	0.5347	0.6027	0.7764
No log	15.0	45	0.6892	0.5711	0.6892	0.8302
No log	16.0	48	0.7100	0.5997	0.7100	0.8426
No log	17.0	51	0.6790	0.5972	0.6790	0.8240
No log	18.0	54	0.7125	0.5946	0.7125	0.8441
No log	19.0	57	0.6809	0.6204	0.6809	0.8252
No log	20.0	60	1.0265	0.4792	1.0265	1.0132
No log	21.0	63	1.0584	0.4649	1.0584	1.0288
No log	22.0	66	1.0532	0.4509	1.0532	1.0262
No log	23.0	69	0.7093	0.5361	0.7093	0.8422
No log	24.0	72	0.6265	0.5732	0.6265	0.7915
No log	25.0	75	0.8568	0.4965	0.8568	0.9256
No log	26.0	78	0.6609	0.5536	0.6609	0.8130
No log	27.0	81	0.6837	0.5802	0.6837	0.8269
No log	28.0	84	1.2066	0.4381	1.2066	1.0984
No log	29.0	87	0.8012	0.5736	0.8012	0.8951
No log	30.0	90	0.6738	0.5837	0.6738	0.8209
No log	31.0	93	0.7156	0.5835	0.7156	0.8459
No log	32.0	96	0.8122	0.5585	0.8122	0.9012
No log	33.0	99	0.8452	0.5315	0.8452	0.9193
No log	34.0	102	0.6265	0.5767	0.6265	0.7915
No log	35.0	105	0.7990	0.5369	0.7990	0.8939
No log	36.0	108	0.6844	0.5596	0.6844	0.8273
No log	37.0	111	0.7406	0.5836	0.7406	0.8606
No log	38.0	114	0.6874	0.5890	0.6874	0.8291
No log	39.0	117	0.7619	0.5571	0.7619	0.8729
No log	40.0	120	0.7120	0.5635	0.7120	0.8438
No log	41.0	123	0.7201	0.5389	0.7201	0.8486
No log	42.0	126	0.7377	0.5630	0.7377	0.8589
No log	43.0	129	0.6664	0.5801	0.6664	0.8164
No log	44.0	132	0.7504	0.5875	0.7504	0.8662
No log	45.0	135	0.6927	0.5787	0.6927	0.8323
No log	46.0	138	0.7492	0.5545	0.7492	0.8656
No log	47.0	141	0.7761	0.5608	0.7761	0.8810
No log	48.0	144	0.6981	0.5691	0.6981	0.8355
No log	49.0	147	0.6815	0.5700	0.6815	0.8255

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV21_k3_task1_organization_k3_k3_fold4

ASAP_FineTuningBERT_AugV21_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_AugV21_k3_task1_organization_k3_k3_fold4