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	11.4250	0.0168	11.4233	3.3798
No log	2.0	4	9.4910	0.0036	9.4893	3.0805
No log	3.0	6	7.0297	0.0	7.0283	2.6511
No log	4.0	8	5.2872	0.0216	5.2860	2.2991
No log	5.0	10	4.2701	0.0076	4.2690	2.0662
No log	6.0	12	3.1020	0.0	3.1010	1.7610
No log	7.0	14	2.2929	0.0799	2.2920	1.5139
No log	8.0	16	1.8355	0.0417	1.8348	1.3545
No log	9.0	18	1.4256	0.0202	1.4249	1.1937
No log	10.0	20	1.1345	0.0202	1.1339	1.0649
No log	11.0	22	0.9744	0.0335	0.9739	0.9869
No log	12.0	24	1.0132	0.0400	1.0128	1.0064
No log	13.0	26	0.8158	0.3401	0.8154	0.9030
No log	14.0	28	0.7160	0.4281	0.7157	0.8460
No log	15.0	30	0.7626	0.4339	0.7624	0.8732
No log	16.0	32	0.9023	0.3580	0.9021	0.9498
No log	17.0	34	0.6734	0.5141	0.6733	0.8205
No log	18.0	36	0.7662	0.4859	0.7661	0.8753
No log	19.0	38	1.0740	0.3132	1.0741	1.0364
No log	20.0	40	0.6180	0.5284	0.6182	0.7862
No log	21.0	42	0.6016	0.5476	0.6018	0.7757
No log	22.0	44	0.8064	0.4625	0.8068	0.8982
No log	23.0	46	0.6064	0.5266	0.6066	0.7788
No log	24.0	48	0.6201	0.5280	0.6204	0.7876
No log	25.0	50	0.7277	0.5024	0.7282	0.8534
No log	26.0	52	0.6562	0.5432	0.6565	0.8103
No log	27.0	54	0.6511	0.5251	0.6514	0.8071
No log	28.0	56	0.7769	0.4890	0.7775	0.8817
No log	29.0	58	0.7439	0.5152	0.7445	0.8628
No log	30.0	60	0.6703	0.5463	0.6706	0.8189
No log	31.0	62	0.8255	0.5076	0.8260	0.9089
No log	32.0	64	0.8348	0.4815	0.8354	0.9140
No log	33.0	66	0.6820	0.5450	0.6824	0.8261
No log	34.0	68	0.7685	0.4991	0.7690	0.8769
No log	35.0	70	0.7883	0.4986	0.7888	0.8882
No log	36.0	72	0.6871	0.5085	0.6875	0.8291
No log	37.0	74	0.6952	0.5164	0.6956	0.8340
No log	38.0	76	0.7454	0.4920	0.7459	0.8637
No log	39.0	78	0.6920	0.4985	0.6924	0.8321
No log	40.0	80	0.7005	0.5238	0.7008	0.8371
No log	41.0	82	0.7529	0.4876	0.7534	0.8680

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_nosemantic_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

ASAP_nosemantic_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_nosemantic_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3