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	8.0685	0.0	8.0685	2.8405
No log	2.0	6	6.7041	0.0	6.7041	2.5892
No log	3.0	9	5.3538	0.0115	5.3538	2.3138
No log	4.0	12	4.1762	0.0039	4.1762	2.0436
No log	5.0	15	2.9789	0.0	2.9789	1.7259
No log	6.0	18	1.9914	0.0484	1.9914	1.4112
No log	7.0	21	1.3701	0.0316	1.3701	1.1705
No log	8.0	24	1.0130	0.0316	1.0130	1.0065
No log	9.0	27	0.8503	0.0807	0.8503	0.9221
No log	10.0	30	0.8710	0.3242	0.8710	0.9333
No log	11.0	33	0.7213	0.4333	0.7213	0.8493
No log	12.0	36	1.0238	0.3861	1.0238	1.0118
No log	13.0	39	0.5915	0.4731	0.5915	0.7691
No log	14.0	42	0.5827	0.5314	0.5827	0.7633
No log	15.0	45	0.5134	0.5273	0.5134	0.7165
No log	16.0	48	0.5057	0.5380	0.5057	0.7111
No log	17.0	51	0.7570	0.3313	0.7570	0.8700
No log	18.0	54	0.6669	0.3636	0.6669	0.8166
No log	19.0	57	0.5038	0.5266	0.5038	0.7098
No log	20.0	60	0.7600	0.4087	0.7600	0.8718
No log	21.0	63	0.7777	0.4660	0.7777	0.8819
No log	22.0	66	0.4944	0.5870	0.4944	0.7031
No log	23.0	69	0.8738	0.4274	0.8738	0.9348
No log	24.0	72	0.8018	0.4828	0.8018	0.8955
No log	25.0	75	0.6187	0.5879	0.6187	0.7866
No log	26.0	78	1.0855	0.3980	1.0855	1.0419
No log	27.0	81	0.9449	0.3858	0.9449	0.9721
No log	28.0	84	0.5884	0.6125	0.5884	0.7671
No log	29.0	87	0.5860	0.6248	0.5860	0.7655
No log	30.0	90	0.9304	0.4232	0.9304	0.9646
No log	31.0	93	0.9066	0.4592	0.9066	0.9522
No log	32.0	96	0.5489	0.6307	0.5489	0.7408
No log	33.0	99	1.2642	0.3910	1.2642	1.1244
No log	34.0	102	1.2171	0.3927	1.2171	1.1032
No log	35.0	105	0.5914	0.6073	0.5914	0.7690
No log	36.0	108	0.7629	0.5618	0.7629	0.8735
No log	37.0	111	0.7377	0.5791	0.7377	0.8589
No log	38.0	114	0.9486	0.4517	0.9486	0.9740
No log	39.0	117	0.9908	0.4572	0.9908	0.9954
No log	40.0	120	0.6191	0.6042	0.6191	0.7868
No log	41.0	123	1.2714	0.4118	1.2714	1.1276
No log	42.0	126	1.0934	0.4350	1.0934	1.0457
No log	43.0	129	0.6462	0.5989	0.6462	0.8039
No log	44.0	132	1.1780	0.4306	1.1780	1.0853
No log	45.0	135	0.8644	0.5026	0.8644	0.9297
No log	46.0	138	0.9717	0.4580	0.9717	0.9858
No log	47.0	141	0.8618	0.4968	0.8618	0.9283
No log	48.0	144	0.8758	0.4994	0.8758	0.9359
No log	49.0	147	0.7310	0.5263	0.7310	0.8550
No log	50.0	150	0.8476	0.4980	0.8476	0.9206
No log	51.0	153	0.6966	0.5884	0.6966	0.8346
No log	52.0	156	0.6077	0.5884	0.6077	0.7795

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold0

Version2ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold0