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	9.9759	-0.0002	9.9733	3.1581
No log	2.0	2	9.4020	0.0	9.3996	3.0659
No log	3.0	3	8.5632	0.0	8.5607	2.9259
No log	4.0	4	7.6582	0.0	7.6557	2.7669
No log	5.0	5	6.8327	0.0	6.8304	2.6135
No log	6.0	6	6.0500	0.0	6.0478	2.4592
No log	7.0	7	5.3527	0.0537	5.3507	2.3132
No log	8.0	8	4.7962	0.0167	4.7942	2.1896
No log	9.0	9	4.3422	0.0040	4.3403	2.0833
No log	10.0	10	3.9557	0.0	3.9539	1.9884
No log	11.0	11	3.5205	0.0	3.5188	1.8758
No log	12.0	12	3.1319	0.0	3.1301	1.7692
No log	13.0	13	2.8069	0.0	2.8052	1.6749
No log	14.0	14	2.5270	0.0	2.5254	1.5891
No log	15.0	15	2.2963	0.1035	2.2947	1.5148
No log	16.0	16	2.0898	0.1036	2.0882	1.4451
No log	17.0	17	1.9028	0.0607	1.9012	1.3788
No log	18.0	18	1.7412	0.0315	1.7397	1.3190
No log	19.0	19	1.5679	0.0106	1.5664	1.2516
No log	20.0	20	1.4188	0.0106	1.4173	1.1905
No log	21.0	21	1.2968	0.0211	1.2954	1.1382
No log	22.0	22	1.2041	0.0106	1.2027	1.0967
No log	23.0	23	1.1134	0.0106	1.1120	1.0545
No log	24.0	24	1.0239	0.0211	1.0226	1.0112
No log	25.0	25	0.9749	0.0315	0.9736	0.9867
No log	26.0	26	0.8914	0.0366	0.8901	0.9435
No log	27.0	27	0.8525	0.2152	0.8513	0.9227
No log	28.0	28	0.7918	0.3737	0.7906	0.8892
No log	29.0	29	0.7154	0.4711	0.7143	0.8452
No log	30.0	30	0.6751	0.4883	0.6740	0.8210
No log	31.0	31	0.6337	0.5064	0.6327	0.7954
No log	32.0	32	0.6172	0.5562	0.6161	0.7849
No log	33.0	33	0.5963	0.5476	0.5953	0.7715
No log	34.0	34	0.5805	0.5603	0.5795	0.7612
No log	35.0	35	0.5737	0.5824	0.5726	0.7567
No log	36.0	36	0.5558	0.5711	0.5547	0.7448
No log	37.0	37	0.5351	0.5655	0.5340	0.7308
No log	38.0	38	0.5478	0.5746	0.5467	0.7394
No log	39.0	39	0.5513	0.5597	0.5501	0.7417
No log	40.0	40	0.5373	0.5441	0.5361	0.7322
No log	41.0	41	0.5493	0.5168	0.5482	0.7404
No log	42.0	42	0.5519	0.5174	0.5507	0.7421
No log	43.0	43	0.6060	0.5255	0.6046	0.7776
No log	44.0	44	0.6158	0.5169	0.6143	0.7838
No log	45.0	45	0.5884	0.5226	0.5872	0.7663
No log	46.0	46	0.6367	0.4946	0.6356	0.7972
No log	47.0	47	0.6530	0.5045	0.6520	0.8074
No log	48.0	48	0.6096	0.5516	0.6085	0.7801
No log	49.0	49	0.6423	0.5544	0.6410	0.8006
No log	50.0	50	0.6914	0.5339	0.6899	0.8306
No log	51.0	51	0.6518	0.5457	0.6504	0.8065
No log	52.0	52	0.6000	0.5591	0.5990	0.7739
No log	53.0	53	0.6559	0.5615	0.6550	0.8093
No log	54.0	54	0.6911	0.5413	0.6903	0.8309
No log	55.0	55	0.6515	0.5627	0.6507	0.8066
No log	56.0	56	0.5979	0.5539	0.5971	0.7727
No log	57.0	57	0.5931	0.5801	0.5921	0.7695
No log	58.0	58	0.6019	0.5790	0.6009	0.7752
No log	59.0	59	0.6182	0.5786	0.6173	0.7857
No log	60.0	60	0.6348	0.5826	0.6340	0.7962
No log	61.0	61	0.6136	0.5980	0.6128	0.7828
No log	62.0	62	0.5925	0.5787	0.5917	0.7692
No log	63.0	63	0.5841	0.5884	0.5833	0.7637
No log	64.0	64	0.5859	0.6032	0.5851	0.7649
No log	65.0	65	0.5859	0.5939	0.5851	0.7649
No log	66.0	66	0.5958	0.5748	0.5950	0.7714
No log	67.0	67	0.6040	0.5632	0.6031	0.7766
No log	68.0	68	0.6189	0.5766	0.6179	0.7861
No log	69.0	69	0.6267	0.5577	0.6257	0.7910
No log	70.0	70	0.6203	0.5605	0.6193	0.7870
No log	71.0	71	0.6166	0.5568	0.6158	0.7847
No log	72.0	72	0.6110	0.5768	0.6101	0.7811
No log	73.0	73	0.5995	0.5730	0.5986	0.7737
No log	74.0	74	0.6007	0.5743	0.5998	0.7745
No log	75.0	75	0.6185	0.5734	0.6175	0.7858
No log	76.0	76	0.6281	0.5591	0.6271	0.7919
No log	77.0	77	0.6254	0.5502	0.6244	0.7902
No log	78.0	78	0.6275	0.5534	0.6265	0.7915
No log	79.0	79	0.6405	0.5695	0.6397	0.7998
No log	80.0	80	0.6489	0.5750	0.6481	0.8050
No log	81.0	81	0.6431	0.5653	0.6422	0.8014
No log	82.0	82	0.6377	0.5401	0.6368	0.7980
No log	83.0	83	0.6361	0.5277	0.6352	0.7970
No log	84.0	84	0.6385	0.5410	0.6375	0.7985
No log	85.0	85	0.6482	0.5368	0.6471	0.8045
No log	86.0	86	0.6545	0.5332	0.6534	0.8083
No log	87.0	87	0.6599	0.5399	0.6589	0.8117
No log	88.0	88	0.6653	0.5281	0.6642	0.8150
No log	89.0	89	0.6713	0.5482	0.6703	0.8187
No log	90.0	90	0.6786	0.5461	0.6777	0.8232
No log	91.0	91	0.6836	0.5473	0.6827	0.8262
No log	92.0	92	0.6820	0.5459	0.6811	0.8253
No log	93.0	93	0.6777	0.5451	0.6767	0.8226
No log	94.0	94	0.6733	0.5296	0.6722	0.8199

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_fold1

BERT_V8_sp10_lw20_ex200_lo100_k1_k1_fold1

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_fold1