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	10.1480	-0.0008	10.1481	3.1856
No log	2.0	4	7.2177	0.0	7.2181	2.6866
No log	3.0	6	5.0249	0.0236	5.0255	2.2418
No log	4.0	8	4.2874	0.0	4.2876	2.0707
No log	5.0	10	3.2008	0.0	3.2012	1.7892
No log	6.0	12	3.0402	0.0	3.0406	1.7437
No log	7.0	14	2.4064	0.0319	2.4069	1.5514
No log	8.0	16	1.5971	0.0107	1.5975	1.2639
No log	9.0	18	1.2350	0.0	1.2355	1.1115
No log	10.0	20	1.0071	0.0	1.0075	1.0038
No log	11.0	22	0.8901	0.0129	0.8904	0.9436
No log	12.0	24	0.8297	0.2975	0.8300	0.9110
No log	13.0	26	0.8694	0.1045	0.8697	0.9326
No log	14.0	28	1.1704	0.1414	1.1708	1.0820
No log	15.0	30	1.0980	0.1709	1.0983	1.0480
No log	16.0	32	0.7812	0.3194	0.7815	0.8840
No log	17.0	34	0.6500	0.4811	0.6502	0.8063
No log	18.0	36	0.6383	0.5001	0.6385	0.7990
No log	19.0	38	0.7238	0.4928	0.7238	0.8508
No log	20.0	40	0.5394	0.5115	0.5394	0.7344
No log	21.0	42	0.5236	0.5344	0.5234	0.7235
No log	22.0	44	0.6532	0.4838	0.6529	0.8080
No log	23.0	46	0.5214	0.5307	0.5210	0.7218
No log	24.0	48	0.5695	0.4548	0.5691	0.7544
No log	25.0	50	0.5319	0.4922	0.5313	0.7289
No log	26.0	52	0.6469	0.4761	0.6463	0.8039
No log	27.0	54	0.5677	0.5080	0.5671	0.7531
No log	28.0	56	0.6679	0.4949	0.6672	0.8168
No log	29.0	58	0.6987	0.4936	0.6979	0.8354
No log	30.0	60	0.5427	0.5886	0.5418	0.7361
No log	31.0	62	0.6049	0.5408	0.6040	0.7772
No log	32.0	64	0.5776	0.5776	0.5766	0.7593
No log	33.0	66	0.5641	0.5764	0.5631	0.7504
No log	34.0	68	0.6006	0.5737	0.5998	0.7745
No log	35.0	70	0.5896	0.5726	0.5888	0.7674
No log	36.0	72	0.6554	0.5372	0.6545	0.8090
No log	37.0	74	0.7456	0.5251	0.7446	0.8629
No log	38.0	76	0.5752	0.5893	0.5743	0.7578
No log	39.0	78	0.8994	0.4434	0.8985	0.9479
No log	40.0	80	0.8150	0.4685	0.8141	0.9023
No log	41.0	82	0.5577	0.6046	0.5567	0.7461
No log	42.0	84	0.6701	0.5458	0.6691	0.8180
No log	43.0	86	0.5836	0.5541	0.5827	0.7634
No log	44.0	88	0.5916	0.5488	0.5909	0.7687
No log	45.0	90	0.5783	0.5462	0.5775	0.7599
No log	46.0	92	0.6120	0.5485	0.6110	0.7817
No log	47.0	94	0.6019	0.5468	0.6009	0.7752
No log	48.0	96	0.5934	0.5558	0.5926	0.7698
No log	49.0	98	0.5932	0.5394	0.5924	0.7697
No log	50.0	100	0.6301	0.5248	0.6293	0.7933
No log	51.0	102	0.5915	0.5088	0.5908	0.7686
No log	52.0	104	0.5894	0.4849	0.5887	0.7673
No log	53.0	106	0.5576	0.5375	0.5568	0.7462
No log	54.0	108	0.6256	0.5593	0.6247	0.7904
No log	55.0	110	0.5944	0.5672	0.5934	0.7704
No log	56.0	112	0.5990	0.5550	0.5980	0.7733

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_sp060_lw010_fold2

Trial3BERT_AugV8_k1_task1_organization_sp060_lw010_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp060_lw010_fold2