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	9.6846	0.0	9.6850	3.1121
No log	2.0	4	9.2217	0.0	9.2218	3.0367
No log	3.0	6	8.7399	0.0	8.7401	2.9564
No log	4.0	8	7.5500	0.0	7.5501	2.7477
No log	5.0	10	6.5009	0.0	6.5011	2.5497
No log	6.0	12	5.4515	0.0039	5.4518	2.3349
No log	7.0	14	4.6823	0.0039	4.6826	2.1639
No log	8.0	16	3.7870	0.0	3.7874	1.9461
No log	9.0	18	3.2340	0.0	3.2344	1.7984
No log	10.0	20	2.8503	0.0	2.8507	1.6884
No log	11.0	22	2.4276	0.0773	2.4280	1.5582
No log	12.0	24	2.0555	0.0387	2.0559	1.4338
No log	13.0	26	1.7757	0.0241	1.7761	1.3327
No log	14.0	28	1.5855	0.0107	1.5860	1.2594
No log	15.0	30	1.4319	0.0107	1.4323	1.1968
No log	16.0	32	1.3061	0.0107	1.3065	1.1430
No log	17.0	34	1.3112	0.0136	1.3116	1.1453
No log	18.0	36	1.0032	0.0	1.0037	1.0018
No log	19.0	38	0.9747	0.0136	0.9750	0.9874
No log	20.0	40	1.4969	0.1278	1.4970	1.2235
No log	21.0	42	1.3713	0.1466	1.3714	1.1711
No log	22.0	44	1.2263	0.1759	1.2261	1.1073
No log	23.0	46	1.5156	0.1822	1.5152	1.2309
No log	24.0	48	1.6409	0.1954	1.6403	1.2808
No log	25.0	50	1.0536	0.3358	1.0529	1.0261
No log	26.0	52	0.9147	0.3900	0.9140	0.9560
No log	27.0	54	1.1816	0.3022	1.1806	1.0865
No log	28.0	56	1.3179	0.2578	1.3167	1.1475
No log	29.0	58	1.0225	0.3564	1.0210	1.0104
No log	30.0	60	1.6230	0.2368	1.6213	1.2733
No log	31.0	62	1.6320	0.2420	1.6301	1.2768
No log	32.0	64	2.0061	0.1614	2.0048	1.4159
No log	33.0	66	1.3204	0.2494	1.3191	1.1485
No log	34.0	68	0.9105	0.4399	0.9090	0.9534
No log	35.0	70	1.3573	0.2856	1.3556	1.1643
No log	36.0	72	3.0945	0.0583	3.0937	1.7589
No log	37.0	74	3.4638	0.0278	3.4633	1.8610
No log	38.0	76	2.1843	0.1530	2.1831	1.4775
No log	39.0	78	0.8633	0.4577	0.8620	0.9284
No log	40.0	80	0.8007	0.4446	0.7994	0.8941
No log	41.0	82	1.2917	0.2798	1.2902	1.1359
No log	42.0	84	2.3739	0.1191	2.3727	1.5404
No log	43.0	86	2.7083	0.0889	2.7072	1.6454
No log	44.0	88	2.2592	0.1348	2.2577	1.5026
No log	45.0	90	1.4423	0.2558	1.4401	1.2000
No log	46.0	92	1.4816	0.2372	1.4796	1.2164
No log	47.0	94	2.0357	0.1066	2.0344	1.4263
No log	48.0	96	1.9400	0.1016	1.9388	1.3924
No log	49.0	98	1.4558	0.1761	1.4545	1.2060
No log	50.0	100	1.6816	0.1756	1.6804	1.2963
No log	51.0	102	1.9256	0.1273	1.9246	1.3873
No log	52.0	104	1.5823	0.1821	1.5812	1.2575
No log	53.0	106	1.5855	0.1721	1.5844	1.2587
No log	54.0	108	1.6386	0.1713	1.6374	1.2796

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_lw060_fold2

BERT_AugV8_k1_task1_organization_sp010_lw060_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k1_task1_organization_sp010_lw060_fold2