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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	9.6436	0.0055	9.6436	3.1054
No log	2.0	4	7.1806	0.0018	7.1806	2.6797
No log	3.0	6	5.2097	0.0453	5.2097	2.2825
No log	4.0	8	4.1448	0.0118	4.1448	2.0359
No log	5.0	10	3.3973	0.0079	3.3973	1.8432
No log	6.0	12	2.9727	0.0040	2.9727	1.7242
No log	7.0	14	2.2322	0.0868	2.2322	1.4941
No log	8.0	16	1.8290	0.0420	1.8290	1.3524
No log	9.0	18	1.4071	0.0420	1.4071	1.1862
No log	10.0	20	1.4317	0.0212	1.4317	1.1965
No log	11.0	22	1.8074	0.0190	1.8074	1.3444
No log	12.0	24	1.6267	0.0212	1.6267	1.2754
No log	13.0	26	1.0444	0.0212	1.0444	1.0219
No log	14.0	28	0.9201	0.0427	0.9201	0.9592
No log	15.0	30	1.0029	0.0420	1.0029	1.0014
No log	16.0	32	0.8478	0.1707	0.8478	0.9208
No log	17.0	34	0.7160	0.4174	0.7160	0.8461
No log	18.0	36	0.7307	0.3658	0.7307	0.8548
No log	19.0	38	0.6499	0.4324	0.6499	0.8062
No log	20.0	40	0.5865	0.4968	0.5865	0.7658
No log	21.0	42	0.5686	0.5660	0.5686	0.7541
No log	22.0	44	0.6886	0.5682	0.6886	0.8298
No log	23.0	46	0.6159	0.6042	0.6159	0.7848
No log	24.0	48	0.5296	0.5865	0.5296	0.7278
No log	25.0	50	0.4808	0.6016	0.4808	0.6934
No log	26.0	52	0.4840	0.5430	0.4840	0.6957
No log	27.0	54	0.4838	0.5407	0.4838	0.6955
No log	28.0	56	0.4697	0.5821	0.4697	0.6854
No log	29.0	58	0.4878	0.5191	0.4878	0.6984
No log	30.0	60	0.6458	0.4692	0.6458	0.8036
No log	31.0	62	0.5250	0.5498	0.5250	0.7246
No log	32.0	64	0.5262	0.5579	0.5262	0.7254
No log	33.0	66	0.6418	0.5891	0.6418	0.8011
No log	34.0	68	0.5379	0.6279	0.5379	0.7334
No log	35.0	70	0.4796	0.6359	0.4796	0.6925
No log	36.0	72	0.5013	0.6521	0.5013	0.7080
No log	37.0	74	0.6117	0.6221	0.6117	0.7821
No log	38.0	76	0.6219	0.6034	0.6219	0.7886
No log	39.0	78	0.5350	0.6283	0.5350	0.7314
No log	40.0	80	0.6021	0.6417	0.6021	0.7759
No log	41.0	82	0.5340	0.6359	0.5340	0.7307
No log	42.0	84	0.5192	0.6501	0.5192	0.7205
No log	43.0	86	0.6012	0.6385	0.6012	0.7753
No log	44.0	88	0.5656	0.6579	0.5656	0.7520
No log	45.0	90	0.5317	0.6706	0.5317	0.7292
No log	46.0	92	0.5586	0.6714	0.5586	0.7474
No log	47.0	94	0.5108	0.6556	0.5108	0.7147
No log	48.0	96	0.5116	0.6302	0.5116	0.7152
No log	49.0	98	0.4980	0.6647	0.4980	0.7057
No log	50.0	100	0.8345	0.5747	0.8345	0.9135
No log	51.0	102	0.9170	0.5448	0.9170	0.9576
No log	52.0	104	0.6007	0.5851	0.6007	0.7751
No log	53.0	106	0.5429	0.5892	0.5429	0.7368
No log	54.0	108	0.5603	0.6504	0.5603	0.7485
No log	55.0	110	0.6236	0.6598	0.6236	0.7897
No log	56.0	112	0.5531	0.6765	0.5531	0.7437
No log	57.0	114	0.5587	0.6646	0.5587	0.7475
No log	58.0	116	0.5709	0.6664	0.5709	0.7556
No log	59.0	118	0.5928	0.6622	0.5928	0.7699
No log	60.0	120	0.6159	0.6692	0.6159	0.7848
No log	61.0	122	0.6287	0.6392	0.6287	0.7929
No log	62.0	124	0.5844	0.6191	0.5844	0.7645
No log	63.0	126	0.7097	0.6155	0.7097	0.8425
No log	64.0	128	0.6926	0.5972	0.6926	0.8322
No log	65.0	130	0.5250	0.5985	0.5250	0.7246
No log	66.0	132	0.5325	0.5829	0.5325	0.7297
No log	67.0	134	0.5375	0.5840	0.5375	0.7331
No log	68.0	136	0.5440	0.5863	0.5440	0.7376
No log	69.0	138	0.6675	0.6055	0.6675	0.8170
No log	70.0	140	0.7091	0.6002	0.7091	0.8421
No log	71.0	142	0.6088	0.6307	0.6088	0.7802

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial2BERT_AugV8_k1_task1_organization_sp010_lw020_fold4

Trial2BERT_AugV8_k1_task1_organization_sp010_lw020_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial2BERT_AugV8_k1_task1_organization_sp010_lw020_fold4