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	2	9.3025	0.0055	9.3025	3.0500
No log	2.0	4	8.4858	0.0018	8.4858	2.9130
No log	3.0	6	7.5297	0.0	7.5297	2.7440
No log	4.0	8	6.3659	0.0	6.3659	2.5231
No log	5.0	10	5.3323	0.0118	5.3323	2.3092
No log	6.0	12	4.4947	0.0040	4.4947	2.1201
No log	7.0	14	3.7670	0.0040	3.7670	1.9409
No log	8.0	16	3.1495	0.0040	3.1495	1.7747
No log	9.0	18	2.7176	0.0040	2.7176	1.6485
No log	10.0	20	2.2487	0.1378	2.2487	1.4996
No log	11.0	22	2.0480	0.1204	2.0480	1.4311
No log	12.0	24	2.1180	0.1374	2.1180	1.4553
No log	13.0	26	1.5758	0.0878	1.5758	1.2553
No log	14.0	28	1.3832	0.0420	1.3832	1.1761
No log	15.0	30	1.2098	0.0771	1.2098	1.0999
No log	16.0	32	1.1834	0.1575	1.1834	1.0878
No log	17.0	34	1.0218	0.1469	1.0218	1.0109
No log	18.0	36	0.8108	0.2834	0.8108	0.9004
No log	19.0	38	0.7178	0.4955	0.7178	0.8472
No log	20.0	40	0.7561	0.5172	0.7561	0.8695
No log	21.0	42	1.0369	0.3575	1.0369	1.0183
No log	22.0	44	0.7528	0.5352	0.7528	0.8677
No log	23.0	46	1.0354	0.4069	1.0354	1.0175
No log	24.0	48	1.1722	0.3553	1.1722	1.0827
No log	25.0	50	0.6645	0.5574	0.6645	0.8152
No log	26.0	52	0.5787	0.5351	0.5787	0.7607
No log	27.0	54	0.6980	0.5504	0.6980	0.8355
No log	28.0	56	1.7836	0.3001	1.7836	1.3355
No log	29.0	58	0.9658	0.4887	0.9658	0.9827
No log	30.0	60	0.5997	0.5146	0.5997	0.7744
No log	31.0	62	0.5719	0.5365	0.5719	0.7562
No log	32.0	64	1.1124	0.3710	1.1124	1.0547
No log	33.0	66	1.2141	0.3704	1.2141	1.1018
No log	34.0	68	0.6044	0.5405	0.6044	0.7775
No log	35.0	70	0.7436	0.4341	0.7436	0.8623
No log	36.0	72	0.6783	0.4863	0.6783	0.8236
No log	37.0	74	0.7441	0.5593	0.7441	0.8626
No log	38.0	76	1.0757	0.4623	1.0757	1.0372
No log	39.0	78	0.6023	0.5609	0.6023	0.7761
No log	40.0	80	0.7488	0.4842	0.7488	0.8653
No log	41.0	82	0.8101	0.4894	0.8101	0.9000
No log	42.0	84	0.6347	0.5244	0.6347	0.7966
No log	43.0	86	0.5907	0.5430	0.5907	0.7686
No log	44.0	88	0.5609	0.5776	0.5609	0.7489
No log	45.0	90	0.5556	0.5980	0.5556	0.7454
No log	46.0	92	0.5906	0.6228	0.5906	0.7685
No log	47.0	94	0.6202	0.6139	0.6202	0.7875
No log	48.0	96	0.6194	0.6226	0.6194	0.7870
No log	49.0	98	1.1778	0.4021	1.1778	1.0853
No log	50.0	100	1.4184	0.3322	1.4184	1.1910
No log	51.0	102	0.7337	0.5391	0.7337	0.8566
No log	52.0	104	0.7513	0.5322	0.7513	0.8668
No log	53.0	106	0.7689	0.5179	0.7689	0.8769
No log	54.0	108	0.6059	0.5769	0.6059	0.7784
No log	55.0	110	0.6299	0.5489	0.6299	0.7937
No log	56.0	112	0.5951	0.5926	0.5951	0.7714
No log	57.0	114	0.7240	0.5284	0.7240	0.8509
No log	58.0	116	0.8033	0.5126	0.8033	0.8963
No log	59.0	118	0.6249	0.6019	0.6249	0.7905
No log	60.0	120	0.7020	0.5068	0.7020	0.8379
No log	61.0	122	0.6915	0.5267	0.6915	0.8316

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial3BERT_AugV8_k1_task1_organization_sp040_lw010_fold4

Trial3BERT_AugV8_k1_task1_organization_sp040_lw010_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp040_lw010_fold4