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	7.8274	0.0	7.8274	2.7977
No log	2.0	6	4.7883	0.0232	4.7883	2.1882
No log	3.0	9	2.8544	0.0246	2.8544	1.6895
No log	4.0	12	1.8867	0.0672	1.8867	1.3736
No log	5.0	15	1.2611	0.0316	1.2611	1.1230
No log	6.0	18	0.9388	0.1100	0.9388	0.9689
No log	7.0	21	0.7517	0.2361	0.7517	0.8670
No log	8.0	24	0.7191	0.1471	0.7191	0.8480
No log	9.0	27	0.7768	0.3232	0.7768	0.8814
No log	10.0	30	0.6204	0.3341	0.6204	0.7877
No log	11.0	33	0.5663	0.3643	0.5663	0.7525
No log	12.0	36	0.5908	0.4753	0.5908	0.7686
No log	13.0	39	0.5949	0.4489	0.5949	0.7713
No log	14.0	42	0.5473	0.4998	0.5473	0.7398
No log	15.0	45	0.5850	0.5127	0.5850	0.7649
No log	16.0	48	0.5340	0.5333	0.5340	0.7307
No log	17.0	51	0.5250	0.5651	0.5250	0.7245
No log	18.0	54	0.5252	0.6048	0.5252	0.7247
No log	19.0	57	0.6421	0.5237	0.6421	0.8013
No log	20.0	60	0.5777	0.5829	0.5777	0.7601
No log	21.0	63	0.5943	0.5202	0.5943	0.7709
No log	22.0	66	0.5754	0.4791	0.5754	0.7586
No log	23.0	69	0.5611	0.5194	0.5611	0.7491
No log	24.0	72	0.6853	0.4734	0.6853	0.8279
No log	25.0	75	0.5521	0.5161	0.5521	0.7431
No log	26.0	78	0.5943	0.5186	0.5943	0.7709
No log	27.0	81	0.5765	0.5210	0.5765	0.7593
No log	28.0	84	0.6473	0.4846	0.6473	0.8046
No log	29.0	87	0.5793	0.5431	0.5793	0.7611
No log	30.0	90	0.7745	0.4251	0.7745	0.8800
No log	31.0	93	0.6176	0.5261	0.6176	0.7859
No log	32.0	96	0.6386	0.5256	0.6386	0.7991
No log	33.0	99	0.6151	0.5241	0.6151	0.7843
No log	34.0	102	0.5976	0.5035	0.5976	0.7731
No log	35.0	105	0.6956	0.4764	0.6956	0.8341
No log	36.0	108	0.5901	0.5595	0.5901	0.7682
No log	37.0	111	0.7727	0.4408	0.7727	0.8790
No log	38.0	114	0.7331	0.4496	0.7331	0.8562
No log	39.0	117	0.6479	0.5092	0.6479	0.8050
No log	40.0	120	0.7791	0.4134	0.7791	0.8826
No log	41.0	123	0.5938	0.5109	0.5938	0.7706
No log	42.0	126	0.6180	0.5368	0.6180	0.7861
No log	43.0	129	0.7334	0.4422	0.7334	0.8564
No log	44.0	132	0.6046	0.5691	0.6046	0.7775
No log	45.0	135	0.6941	0.4817	0.6941	0.8331
No log	46.0	138	0.6785	0.5005	0.6785	0.8237
No log	47.0	141	0.5866	0.5325	0.5866	0.7659
No log	48.0	144	0.6689	0.4962	0.6689	0.8179

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

genki10/BERT_V8_sp10_lw40_ex50_lo50_k5_k5_fold0

BERT_V8_sp10_lw40_ex50_lo50_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_V8_sp10_lw40_ex50_lo50_k5_k5_fold0