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	3	8.2494	0.0	8.2494	2.8722
No log	2.0	6	6.8239	0.0	6.8239	2.6123
No log	3.0	9	5.5385	0.0112	5.5385	2.3534
No log	4.0	12	4.2753	0.0039	4.2753	2.0677
No log	5.0	15	3.1217	0.0	3.1217	1.7668
No log	6.0	18	2.0646	0.0627	2.0646	1.4369
No log	7.0	21	1.4818	0.0316	1.4818	1.2173
No log	8.0	24	1.3142	0.0316	1.3142	1.1464
No log	9.0	27	1.3379	0.0316	1.3379	1.1567
No log	10.0	30	1.3453	0.0484	1.3453	1.1599
No log	11.0	33	1.5824	0.1448	1.5824	1.2579
No log	12.0	36	1.3526	0.1481	1.3526	1.1630
No log	13.0	39	1.2212	0.1391	1.2212	1.1051
No log	14.0	42	1.3046	0.1703	1.3046	1.1422
No log	15.0	45	1.1778	0.1648	1.1778	1.0853
No log	16.0	48	0.9889	0.2130	0.9889	0.9945
No log	17.0	51	1.0209	0.3200	1.0209	1.0104
No log	18.0	54	0.7711	0.3755	0.7711	0.8781
No log	19.0	57	1.6928	0.1579	1.6928	1.3011
No log	20.0	60	0.9841	0.3098	0.9841	0.9920
No log	21.0	63	1.0722	0.3056	1.0722	1.0355
No log	22.0	66	1.1228	0.2968	1.1228	1.0596
No log	23.0	69	1.3942	0.2547	1.3942	1.1807
No log	24.0	72	1.1926	0.3031	1.1926	1.0921
No log	25.0	75	1.0661	0.3625	1.0661	1.0325
No log	26.0	78	1.1071	0.3556	1.1071	1.0522
No log	27.0	81	1.3244	0.2915	1.3244	1.1508
No log	28.0	84	1.0470	0.3693	1.0470	1.0232
No log	29.0	87	1.0722	0.3350	1.0722	1.0355
No log	30.0	90	0.9122	0.4272	0.9122	0.9551
No log	31.0	93	1.0458	0.3713	1.0458	1.0226
No log	32.0	96	1.1307	0.3413	1.1307	1.0634
No log	33.0	99	0.9047	0.4042	0.9047	0.9512
No log	34.0	102	0.9644	0.4029	0.9644	0.9820
No log	35.0	105	1.1830	0.3164	1.1830	1.0877
No log	36.0	108	1.0878	0.3400	1.0878	1.0430
No log	37.0	111	1.0345	0.3309	1.0345	1.0171
No log	38.0	114	1.1305	0.3120	1.1305	1.0633
No log	39.0	117	0.9333	0.3907	0.9333	0.9661
No log	40.0	120	1.5243	0.2238	1.5243	1.2346
No log	41.0	123	1.1516	0.2838	1.1516	1.0731
No log	42.0	126	0.7383	0.4428	0.7383	0.8592
No log	43.0	129	1.3301	0.2461	1.3301	1.1533
No log	44.0	132	0.8230	0.4082	0.8230	0.9072
No log	45.0	135	0.9369	0.3582	0.9369	0.9679
No log	46.0	138	1.4797	0.2070	1.4797	1.2164
No log	47.0	141	0.8319	0.3927	0.8319	0.9121
No log	48.0	144	0.9551	0.3365	0.9551	0.9773
No log	49.0	147	1.4180	0.2226	1.4180	1.1908
No log	50.0	150	0.9194	0.3799	0.9194	0.9589
No log	51.0	153	1.3632	0.2658	1.3632	1.1676
No log	52.0	156	1.1800	0.2713	1.1800	1.0863
No log	53.0	159	0.8496	0.3881	0.8496	0.9217
No log	54.0	162	1.3218	0.2309	1.3218	1.1497
No log	55.0	165	0.9173	0.3550	0.9173	0.9578
No log	56.0	168	0.9914	0.3208	0.9914	0.9957
No log	57.0	171	0.9918	0.3242	0.9918	0.9959

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/BERT_AugV8_k3_task1_organization_sp020_lw070_fold0

BERT_AugV8_k3_task1_organization_sp020_lw070_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k3_task1_organization_sp020_lw070_fold0