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	2	9.5499	0.0018	9.5500	3.0903
No log	2.0	4	7.9161	0.0	7.9164	2.8136
No log	3.0	6	7.4475	0.0	7.4477	2.7290
No log	4.0	8	6.1342	0.0118	6.1345	2.4768
No log	5.0	10	4.7755	0.0064	4.7759	2.1854
No log	6.0	12	3.8585	0.0	3.8590	1.9644
No log	7.0	14	3.2234	0.0	3.2241	1.7956
No log	8.0	16	2.3103	0.1108	2.3107	1.5201
No log	9.0	18	1.8540	0.1090	1.8543	1.3617
No log	10.0	20	1.5368	0.0475	1.5372	1.2398
No log	11.0	22	1.4244	0.0527	1.4250	1.1937
No log	12.0	24	1.0420	0.0463	1.0423	1.0209
No log	13.0	26	0.9172	0.0259	0.9175	0.9578
No log	14.0	28	0.9144	0.2748	0.9147	0.9564
No log	15.0	30	1.2022	0.1430	1.2026	1.0966
No log	16.0	32	0.9081	0.1010	0.9084	0.9531
No log	17.0	34	0.6566	0.4162	0.6567	0.8104
No log	18.0	36	0.6219	0.4071	0.6219	0.7886
No log	19.0	38	0.6918	0.4792	0.6918	0.8317
No log	20.0	40	1.0701	0.3734	1.0703	1.0346
No log	21.0	42	1.2463	0.3086	1.2466	1.1165
No log	22.0	44	0.7331	0.4838	0.7332	0.8563
No log	23.0	46	0.5766	0.5113	0.5766	0.7593
No log	24.0	48	0.6900	0.4511	0.6902	0.8308
No log	25.0	50	0.8838	0.3304	0.8841	0.9403
No log	26.0	52	0.7236	0.4115	0.7239	0.8508
No log	27.0	54	0.6496	0.4014	0.6498	0.8061
No log	28.0	56	0.7103	0.3993	0.7106	0.8430
No log	29.0	58	0.8981	0.3691	0.8984	0.9478
No log	30.0	60	0.9044	0.3655	0.9043	0.9510
No log	31.0	62	0.9906	0.3555	0.9905	0.9952
No log	32.0	64	1.1480	0.3158	1.1481	1.0715
No log	33.0	66	0.8888	0.3932	0.8894	0.9431
No log	34.0	68	0.6393	0.4469	0.6397	0.7998
No log	35.0	70	0.6208	0.4718	0.6211	0.7881
No log	36.0	72	0.6872	0.4211	0.6874	0.8291
No log	37.0	74	0.7598	0.4165	0.7601	0.8718
No log	38.0	76	0.7903	0.4758	0.7906	0.8892
No log	39.0	78	0.8852	0.4724	0.8857	0.9411
No log	40.0	80	0.8254	0.4549	0.8257	0.9087
No log	41.0	82	0.8214	0.4733	0.8215	0.9064
No log	42.0	84	0.8509	0.4683	0.8513	0.9227
No log	43.0	86	1.1064	0.4276	1.1071	1.0522

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold2

Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold2