learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.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	7.8820	0.0	7.8824	2.8076
No log	2.0	6	6.3895	-0.0003	6.3897	2.5278
No log	3.0	9	5.2083	0.0078	5.2087	2.2823
No log	4.0	12	3.8877	0.0	3.8881	1.9718
No log	5.0	15	2.8893	0.0	2.8897	1.6999
No log	6.0	18	2.3020	-0.0540	2.3025	1.5174
No log	7.0	21	1.8328	0.0664	1.8332	1.3540
No log	8.0	24	1.3896	0.0	1.3903	1.1791
No log	9.0	27	1.6512	0.0774	1.6516	1.2851
No log	10.0	30	1.3417	0.0280	1.3421	1.1585
No log	11.0	33	0.7364	0.2127	0.7367	0.8583
No log	12.0	36	0.6890	0.3973	0.6893	0.8302
No log	13.0	39	1.1431	0.0345	1.1434	1.0693
No log	14.0	42	0.8830	0.1550	0.8832	0.9398
No log	15.0	45	0.6668	0.4607	0.6667	0.8165
No log	16.0	48	0.9401	0.3325	0.9402	0.9697
No log	17.0	51	0.5898	0.5132	0.5898	0.7680
No log	18.0	54	1.1246	0.2642	1.1248	1.0606
No log	19.0	57	0.6946	0.5122	0.6944	0.8333
No log	20.0	60	0.5512	0.5332	0.5507	0.7421
No log	21.0	63	0.6260	0.5040	0.6258	0.7911
No log	22.0	66	0.5591	0.4498	0.5588	0.7476
No log	23.0	69	0.5553	0.4914	0.5552	0.7451
No log	24.0	72	0.5936	0.4952	0.5934	0.7703
No log	25.0	75	0.7584	0.4327	0.7583	0.8708
No log	26.0	78	0.7193	0.4516	0.7191	0.8480
No log	27.0	81	0.6688	0.4343	0.6686	0.8177
No log	28.0	84	0.7998	0.3768	0.7998	0.8943
No log	29.0	87	0.6832	0.4505	0.6829	0.8264
No log	30.0	90	0.7367	0.4435	0.7366	0.8582
No log	31.0	93	0.6695	0.4751	0.6693	0.8181
No log	32.0	96	0.6016	0.5170	0.6013	0.7755
No log	33.0	99	0.7119	0.4541	0.7118	0.8437
No log	34.0	102	0.6857	0.4684	0.6857	0.8281
No log	35.0	105	0.8277	0.3551	0.8278	0.9098
No log	36.0	108	0.6526	0.4999	0.6526	0.8078
No log	37.0	111	0.8739	0.3529	0.8739	0.9348
No log	38.0	114	0.5992	0.4923	0.5990	0.7740
No log	39.0	117	0.6443	0.4864	0.6442	0.8026
No log	40.0	120	0.8082	0.4073	0.8082	0.8990
No log	41.0	123	0.5759	0.4495	0.5758	0.7588
No log	42.0	126	0.6129	0.4607	0.6129	0.7829
No log	43.0	129	0.6405	0.4833	0.6405	0.8003
No log	44.0	132	0.6082	0.4875	0.6081	0.7798
No log	45.0	135	0.7443	0.4329	0.7443	0.8627
No log	46.0	138	0.6058	0.4743	0.6057	0.7783
No log	47.0	141	0.5994	0.4745	0.5993	0.7742
No log	48.0	144	0.5764	0.4898	0.5763	0.7591
No log	49.0	147	0.6567	0.4827	0.6566	0.8103
No log	50.0	150	0.5924	0.4976	0.5922	0.7696

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

genki10/BERT_V8_sp10_lw40_ex30_lo00_k3_k3_fold2

BERT_V8_sp10_lw40_ex30_lo00_k3_k3_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_V8_sp10_lw40_ex30_lo00_k3_k3_fold2