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	4	10.2355	0.0	10.2354	3.1993
No log	2.0	8	7.9367	0.0	7.9367	2.8172
No log	3.0	12	5.2410	0.0137	5.2414	2.2894
No log	4.0	16	3.4712	0.0	3.4716	1.8632
No log	5.0	20	1.9971	0.0422	1.9976	1.4134
No log	6.0	24	1.1855	0.0107	1.1859	1.0890
No log	7.0	28	0.8779	0.0527	0.8783	0.9372
No log	8.0	32	0.8394	0.2206	0.8396	0.9163
No log	9.0	36	1.1413	0.1103	1.1415	1.0684
No log	10.0	40	0.6964	0.4653	0.6966	0.8346
No log	11.0	44	0.7802	0.3896	0.7803	0.8834
No log	12.0	48	1.0524	0.2899	1.0525	1.0259
No log	13.0	52	0.5868	0.4869	0.5868	0.7660
No log	14.0	56	0.6856	0.3960	0.6856	0.8280
No log	15.0	60	0.5884	0.4573	0.5884	0.7671
No log	16.0	64	0.6072	0.4725	0.6072	0.7792
No log	17.0	68	0.9004	0.3194	0.9003	0.9489
No log	18.0	72	0.6587	0.4637	0.6586	0.8116
No log	19.0	76	0.7060	0.4342	0.7058	0.8401
No log	20.0	80	0.7049	0.4471	0.7047	0.8395
No log	21.0	84	0.6564	0.4578	0.6561	0.8100
No log	22.0	88	0.6447	0.4588	0.6445	0.8028
No log	23.0	92	0.7124	0.4166	0.7122	0.8439
No log	24.0	96	0.7668	0.3846	0.7667	0.8756
No log	25.0	100	1.1797	0.2725	1.1794	1.0860
No log	26.0	104	0.5712	0.5159	0.5710	0.7556
No log	27.0	108	0.8290	0.3843	0.8287	0.9103
No log	28.0	112	0.6455	0.4645	0.6452	0.8033
No log	29.0	116	0.8781	0.3575	0.8779	0.9370
No log	30.0	120	1.1338	0.2976	1.1335	1.0647
No log	31.0	124	0.5857	0.4972	0.5855	0.7652
No log	32.0	128	0.8290	0.3678	0.8289	0.9104
No log	33.0	132	0.6591	0.4190	0.6589	0.8117
No log	34.0	136	1.0479	0.3106	1.0476	1.0235
No log	35.0	140	0.6187	0.4740	0.6186	0.7865
No log	36.0	144	1.1625	0.2443	1.1624	1.0782
No log	37.0	148	0.6422	0.4744	0.6422	0.8014
No log	38.0	152	1.3075	0.2112	1.3074	1.1434
No log	39.0	156	0.9658	0.2746	0.9657	0.9827
No log	40.0	160	0.6704	0.4339	0.6703	0.8187
No log	41.0	164	1.2707	0.2673	1.2705	1.1272

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/BERT_AugV8_k5_task1_organization_sp010_lw050_fold2

BERT_AugV8_k5_task1_organization_sp010_lw050_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k5_task1_organization_sp010_lw050_fold2