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	10.2288	0.0037	10.2261	3.1978
No log	2.0	4	9.6792	0.0	9.6766	3.1107
No log	3.0	6	9.2529	0.0	9.2503	3.0414
No log	4.0	8	8.4102	0.0	8.4076	2.8996
No log	5.0	10	6.5581	0.0	6.5559	2.5605
No log	6.0	12	5.2978	0.0260	5.2958	2.3013
No log	7.0	14	4.1659	0.0	4.1639	2.0406
No log	8.0	16	3.3741	0.0	3.3722	1.8363
No log	9.0	18	2.4130	0.0260	2.4113	1.5528
No log	10.0	20	1.7056	0.0443	1.7040	1.3054
No log	11.0	22	1.5420	-0.0013	1.5405	1.2412
No log	12.0	24	1.1706	0.0	1.1692	1.0813
No log	13.0	26	1.1139	0.0211	1.1125	1.0548
No log	14.0	28	1.0681	0.0315	1.0667	1.0328
No log	15.0	30	0.9408	0.0392	0.9395	0.9693
No log	16.0	32	0.8321	0.2291	0.8308	0.9115
No log	17.0	34	1.2881	0.1646	1.2866	1.1343
No log	18.0	36	1.6576	0.1674	1.6559	1.2868
No log	19.0	38	1.1979	0.1908	1.1964	1.0938
No log	20.0	40	1.0827	0.2674	1.0812	1.0398
No log	21.0	42	1.1265	0.2721	1.1249	1.0606
No log	22.0	44	1.5618	0.1980	1.5601	1.2491
No log	23.0	46	1.9570	0.1548	1.9554	1.3984
No log	24.0	48	1.1620	0.3551	1.1606	1.0773
No log	25.0	50	1.4743	0.2739	1.4730	1.2137
No log	26.0	52	2.4136	0.1230	2.4123	1.5532
No log	27.0	54	1.2939	0.3126	1.2927	1.1370
No log	28.0	56	0.8383	0.4394	0.8371	0.9149
No log	29.0	58	1.4099	0.2586	1.4084	1.1868
No log	30.0	60	1.2678	0.2889	1.2663	1.1253
No log	31.0	62	0.8280	0.4481	0.8268	0.9093
No log	32.0	64	0.9952	0.4071	0.9938	0.9969
No log	33.0	66	2.7926	0.1039	2.7903	1.6704
No log	34.0	68	3.2454	0.0875	3.2430	1.8008
No log	35.0	70	1.6533	0.2300	1.6513	1.2850
No log	36.0	72	0.8354	0.4270	0.8343	0.9134
No log	37.0	74	0.8465	0.4395	0.8452	0.9193
No log	38.0	76	1.5994	0.1949	1.5972	1.2638
No log	39.0	78	1.7667	0.2021	1.7645	1.3283
No log	40.0	80	0.9918	0.3406	0.9902	0.9951
No log	41.0	82	0.9460	0.3936	0.9446	0.9719
No log	42.0	84	1.6128	0.2329	1.6109	1.2692
No log	43.0	86	2.6539	0.0884	2.6518	1.6284
No log	44.0	88	2.4550	0.1085	2.4531	1.5662
No log	45.0	90	1.5605	0.2433	1.5588	1.2485
No log	46.0	92	1.0531	0.3652	1.0517	1.0255

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/BERT_AugV8_k1_task1_organization_sp010_lw070_fold1

BERT_AugV8_k1_task1_organization_sp010_lw070_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k1_task1_organization_sp010_lw070_fold1