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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	10.2280	-0.0001	10.2280	3.1981
No log	2.0	2	9.5441	0.0018	9.5441	3.0894
No log	3.0	3	8.5719	0.0018	8.5719	2.9278
No log	4.0	4	7.6867	0.0018	7.6867	2.7725
No log	5.0	5	6.8729	0.0018	6.8729	2.6216
No log	6.0	6	6.0731	0.0052	6.0731	2.4644
No log	7.0	7	5.3394	0.0495	5.3394	2.3107
No log	8.0	8	4.8634	0.0186	4.8634	2.2053
No log	9.0	9	4.3311	0.0118	4.3311	2.0811
No log	10.0	10	3.8697	0.0079	3.8697	1.9672
No log	11.0	11	3.4104	0.0079	3.4104	1.8467
No log	12.0	12	3.0508	0.0040	3.0508	1.7466
No log	13.0	13	2.7508	0.0040	2.7508	1.6585
No log	14.0	14	2.4907	0.0208	2.4907	1.5782
No log	15.0	15	2.2375	0.1836	2.2375	1.4958
No log	16.0	16	2.0029	0.0975	2.0029	1.4152
No log	17.0	17	1.8067	0.0572	1.8067	1.3442
No log	18.0	18	1.6906	0.0795	1.6906	1.3002
No log	19.0	19	1.4969	0.0522	1.4969	1.2235
No log	20.0	20	1.3303	0.0420	1.3303	1.1534
No log	21.0	21	1.2083	0.0420	1.2083	1.0992
No log	22.0	22	1.2018	0.0624	1.2018	1.0963
No log	23.0	23	1.1042	0.0624	1.1042	1.0508
No log	24.0	24	0.9609	0.0624	0.9609	0.9802
No log	25.0	25	0.8860	0.0624	0.8860	0.9413
No log	26.0	26	0.8206	0.2339	0.8206	0.9059
No log	27.0	27	0.8095	0.3070	0.8095	0.8997
No log	28.0	28	0.7974	0.3871	0.7974	0.8930
No log	29.0	29	0.6913	0.4949	0.6913	0.8315
No log	30.0	30	0.6327	0.5242	0.6327	0.7955
No log	31.0	31	0.5938	0.5266	0.5938	0.7706
No log	32.0	32	0.6375	0.5566	0.6375	0.7984
No log	33.0	33	0.6447	0.5625	0.6447	0.8029
No log	34.0	34	0.6300	0.5776	0.6300	0.7937
No log	35.0	35	0.5260	0.5863	0.5260	0.7252
No log	36.0	36	0.5024	0.5742	0.5024	0.7088
No log	37.0	37	0.5260	0.5876	0.5260	0.7252
No log	38.0	38	0.6712	0.5597	0.6712	0.8193
No log	39.0	39	0.6854	0.5562	0.6854	0.8279
No log	40.0	40	0.5628	0.5944	0.5628	0.7502
No log	41.0	41	0.4890	0.5811	0.4890	0.6993
No log	42.0	42	0.4945	0.5556	0.4945	0.7032
No log	43.0	43	0.5057	0.5870	0.5057	0.7111
No log	44.0	44	0.6410	0.5612	0.6410	0.8006
No log	45.0	45	0.7169	0.5126	0.7169	0.8467
No log	46.0	46	0.6423	0.5295	0.6423	0.8015
No log	47.0	47	0.5228	0.5870	0.5228	0.7231
No log	48.0	48	0.5149	0.5689	0.5149	0.7176
No log	49.0	49	0.5297	0.5728	0.5297	0.7278
No log	50.0	50	0.5150	0.5855	0.5150	0.7176
No log	51.0	51	0.5643	0.5488	0.5643	0.7512
No log	52.0	52	0.6171	0.5270	0.6171	0.7856
No log	53.0	53	0.5855	0.5531	0.5855	0.7652
No log	54.0	54	0.5328	0.5752	0.5328	0.7299
No log	55.0	55	0.5333	0.5838	0.5333	0.7302
No log	56.0	56	0.5368	0.5946	0.5368	0.7326
No log	57.0	57	0.5556	0.5935	0.5556	0.7454
No log	58.0	58	0.5567	0.5914	0.5567	0.7461
No log	59.0	59	0.5366	0.6169	0.5366	0.7325
No log	60.0	60	0.5334	0.6285	0.5334	0.7304
No log	61.0	61	0.5408	0.6076	0.5408	0.7354
No log	62.0	62	0.5429	0.5925	0.5429	0.7368
No log	63.0	63	0.5300	0.6212	0.5300	0.7280
No log	64.0	64	0.5312	0.6159	0.5312	0.7288
No log	65.0	65	0.5325	0.6147	0.5325	0.7297
No log	66.0	66	0.5416	0.6148	0.5416	0.7359
No log	67.0	67	0.5624	0.5830	0.5624	0.7499
No log	68.0	68	0.5574	0.5841	0.5574	0.7466
No log	69.0	69	0.5418	0.6314	0.5418	0.7361
No log	70.0	70	0.5423	0.6091	0.5423	0.7364
No log	71.0	71	0.5413	0.6075	0.5413	0.7357
No log	72.0	72	0.5411	0.6450	0.5411	0.7356
No log	73.0	73	0.5494	0.6107	0.5494	0.7412
No log	74.0	74	0.5482	0.6050	0.5482	0.7404
No log	75.0	75	0.5363	0.6268	0.5363	0.7323
No log	76.0	76	0.5317	0.6178	0.5317	0.7292
No log	77.0	77	0.5355	0.6074	0.5355	0.7318
No log	78.0	78	0.5338	0.6094	0.5338	0.7306
No log	79.0	79	0.5296	0.6201	0.5296	0.7278
No log	80.0	80	0.5350	0.5937	0.5350	0.7314
No log	81.0	81	0.5385	0.5808	0.5385	0.7338
No log	82.0	82	0.5510	0.5908	0.5510	0.7423
No log	83.0	83	0.5524	0.5817	0.5524	0.7432
No log	84.0	84	0.5457	0.5986	0.5457	0.7387
No log	85.0	85	0.5417	0.6278	0.5417	0.7360
No log	86.0	86	0.5457	0.6257	0.5457	0.7387
No log	87.0	87	0.5475	0.6257	0.5475	0.7399
No log	88.0	88	0.5454	0.6321	0.5454	0.7385
No log	89.0	89	0.5457	0.6433	0.5457	0.7387
No log	90.0	90	0.5468	0.6354	0.5468	0.7394
No log	91.0	91	0.5531	0.6205	0.5531	0.7437
No log	92.0	92	0.5581	0.6006	0.5581	0.7471
No log	93.0	93	0.5597	0.5978	0.5597	0.7481
No log	94.0	94	0.5581	0.6076	0.5581	0.7471
No log	95.0	95	0.5546	0.6233	0.5546	0.7447
No log	96.0	96	0.5515	0.6274	0.5515	0.7426
No log	97.0	97	0.5499	0.6347	0.5499	0.7416
No log	98.0	98	0.5496	0.6361	0.5496	0.7413
No log	99.0	99	0.5495	0.6368	0.5495	0.7412
No log	100.0	100	0.5494	0.6368	0.5494	0.7412

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/BERT_V8_sp10_lw20_ex200_lo100_k1_k1_fold4

BERT_V8_sp10_lw20_ex200_lo100_k1_k1_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_V8_sp10_lw20_ex200_lo100_k1_k1_fold4