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	10.2095	0.0	10.2071	3.1949
No log	2.0	6	8.0769	0.0	8.0745	2.8416
No log	3.0	9	5.4835	0.0556	5.4812	2.3412
No log	4.0	12	3.0993	0.0	3.0975	1.7600
No log	5.0	15	2.0374	0.1708	2.0356	1.4268
No log	6.0	18	1.2966	0.0315	1.2951	1.1380
No log	7.0	21	1.0230	0.0315	1.0216	1.0107
No log	8.0	24	1.2723	0.0872	1.2708	1.1273
No log	9.0	27	1.0493	0.0850	1.0479	1.0236
No log	10.0	30	0.9860	0.1361	0.9845	0.9922
No log	11.0	33	0.9239	0.2341	0.9222	0.9603
No log	12.0	36	0.8076	0.2951	0.8061	0.8978
No log	13.0	39	0.8172	0.2487	0.8158	0.9032
No log	14.0	42	0.6774	0.3841	0.6760	0.8222
No log	15.0	45	0.8042	0.4189	0.8026	0.8959
No log	16.0	48	0.7268	0.3796	0.7253	0.8517
No log	17.0	51	0.8445	0.3683	0.8428	0.9180
No log	18.0	54	0.7693	0.4041	0.7678	0.8762
No log	19.0	57	0.9142	0.3577	0.9124	0.9552
No log	20.0	60	0.8938	0.3713	0.8921	0.9445
No log	21.0	63	1.5147	0.2167	1.5123	1.2298
No log	22.0	66	0.9377	0.3489	0.9364	0.9677
No log	23.0	69	1.2241	0.2727	1.2219	1.1054
No log	24.0	72	1.0999	0.3352	1.0979	1.0478
No log	25.0	75	1.2173	0.2872	1.2152	1.1023
No log	26.0	78	0.7952	0.4306	0.7938	0.8909
No log	27.0	81	1.2033	0.2659	1.2011	1.0959
No log	28.0	84	0.8162	0.3991	0.8149	0.9027
No log	29.0	87	1.0152	0.3447	1.0132	1.0066
No log	30.0	90	0.7835	0.4212	0.7819	0.8843
No log	31.0	93	1.2858	0.2799	1.2834	1.1329
No log	32.0	96	0.9160	0.3960	0.9139	0.9560
No log	33.0	99	0.8131	0.4205	0.8119	0.9010
No log	34.0	102	1.2046	0.2719	1.2023	1.0965
No log	35.0	105	0.8705	0.3496	0.8687	0.9320
No log	36.0	108	0.9057	0.3713	0.9038	0.9507
No log	37.0	111	1.2654	0.2673	1.2630	1.1238
No log	38.0	114	0.7618	0.4367	0.7603	0.8719
No log	39.0	117	1.0785	0.3135	1.0763	1.0374
No log	40.0	120	0.9250	0.4046	0.9230	0.9607
No log	41.0	123	0.7061	0.4463	0.7047	0.8395
No log	42.0	126	1.2737	0.2804	1.2715	1.1276
No log	43.0	129	0.9765	0.3596	0.9745	0.9872
No log	44.0	132	0.7110	0.4270	0.7097	0.8424
No log	45.0	135	1.1206	0.3042	1.1184	1.0576
No log	46.0	138	0.9253	0.3993	0.9233	0.9609
No log	47.0	141	0.9143	0.3774	0.9124	0.9552
No log	48.0	144	0.8259	0.3981	0.8242	0.9078
No log	49.0	147	1.0773	0.2737	1.0751	1.0369
No log	50.0	150	0.8799	0.3315	0.8783	0.9372
No log	51.0	153	0.9863	0.3193	0.9843	0.9921
No log	52.0	156	0.9200	0.3341	0.9182	0.9582
No log	53.0	159	0.9116	0.3727	0.9098	0.9538
No log	54.0	162	1.0713	0.3420	1.0693	1.0341
No log	55.0	165	0.9525	0.4011	0.9506	0.9750
No log	56.0	168	0.9824	0.3660	0.9804	0.9902

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_sp060_lw010_fold1

BERT_AugV8_k3_task1_organization_sp060_lw010_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k3_task1_organization_sp060_lw010_fold1