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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	10.2689	0.0036	10.2689	3.2045
No log	2.0	4	9.8069	0.0	9.8069	3.1316
No log	3.0	6	8.8063	0.0	8.8063	2.9675
No log	4.0	8	7.7680	0.0	7.7680	2.7871
No log	5.0	10	6.3885	0.0031	6.3885	2.5275
No log	6.0	12	5.3044	0.0194	5.3044	2.3031
No log	7.0	14	4.2229	0.0115	4.2229	2.0550
No log	8.0	16	3.4813	0.0077	3.4813	1.8658
No log	9.0	18	2.6195	0.0276	2.6195	1.6185
No log	10.0	20	1.9612	0.0548	1.9612	1.4004
No log	11.0	22	1.6784	0.0316	1.6784	1.2955
No log	12.0	24	1.2585	0.0316	1.2585	1.1218
No log	13.0	26	1.0033	0.0316	1.0033	1.0017
No log	14.0	28	0.8625	0.2312	0.8625	0.9287
No log	15.0	30	0.7501	0.1471	0.7501	0.8661
No log	16.0	32	0.7251	0.1455	0.7251	0.8516
No log	17.0	34	0.7227	0.1487	0.7227	0.8501
No log	18.0	36	0.8003	0.1397	0.8003	0.8946
No log	19.0	38	0.8746	0.2428	0.8746	0.9352
No log	20.0	40	0.8613	0.3793	0.8613	0.9281
No log	21.0	42	0.6640	0.4613	0.6640	0.8149
No log	22.0	44	0.6794	0.4975	0.6794	0.8243
No log	23.0	46	0.5778	0.6002	0.5778	0.7601
No log	24.0	48	0.6189	0.5859	0.6189	0.7867
No log	25.0	50	0.6857	0.6113	0.6857	0.8281
No log	26.0	52	0.7080	0.6179	0.7080	0.8414
No log	27.0	54	0.8123	0.5965	0.8123	0.9013
No log	28.0	56	0.6693	0.6273	0.6693	0.8181
No log	29.0	58	0.6617	0.6525	0.6617	0.8134
No log	30.0	60	0.7490	0.6030	0.7490	0.8654
No log	31.0	62	0.5611	0.6133	0.5611	0.7491
No log	32.0	64	0.5986	0.6449	0.5986	0.7737
No log	33.0	66	1.1102	0.5393	1.1102	1.0537
No log	34.0	68	0.6684	0.6349	0.6684	0.8176
No log	35.0	70	0.7262	0.5501	0.7262	0.8522
No log	36.0	72	0.5501	0.6205	0.5501	0.7417
No log	37.0	74	0.9212	0.5493	0.9212	0.9598
No log	38.0	76	0.8874	0.5397	0.8874	0.9420
No log	39.0	78	0.5512	0.6543	0.5512	0.7424
No log	40.0	80	0.5965	0.6425	0.5965	0.7723
No log	41.0	82	0.8809	0.5720	0.8809	0.9386
No log	42.0	84	0.7721	0.6070	0.7721	0.8787
No log	43.0	86	0.6086	0.6381	0.6086	0.7801
No log	44.0	88	0.6190	0.6375	0.6190	0.7868
No log	45.0	90	0.6769	0.6467	0.6769	0.8228
No log	46.0	92	0.6266	0.6264	0.6266	0.7916
No log	47.0	94	0.5783	0.6409	0.5783	0.7604
No log	48.0	96	0.7730	0.5676	0.7730	0.8792
No log	49.0	98	0.8993	0.5423	0.8993	0.9483
No log	50.0	100	0.6345	0.6271	0.6345	0.7966
No log	51.0	102	0.5771	0.6368	0.5771	0.7597
No log	52.0	104	0.6024	0.6554	0.6024	0.7762
No log	53.0	106	0.8047	0.6031	0.8047	0.8971
No log	54.0	108	0.7719	0.6077	0.7719	0.8786
No log	55.0	110	0.5611	0.6628	0.5611	0.7491
No log	56.0	112	0.5422	0.6612	0.5422	0.7364
No log	57.0	114	0.6502	0.6283	0.6502	0.8064
No log	58.0	116	0.8434	0.5901	0.8434	0.9184
No log	59.0	118	0.7550	0.6338	0.7550	0.8689
No log	60.0	120	0.6593	0.6170	0.6593	0.8120
No log	61.0	122	0.6580	0.6073	0.6580	0.8112
No log	62.0	124	0.6033	0.6414	0.6033	0.7767
No log	63.0	126	0.6354	0.6294	0.6354	0.7971
No log	64.0	128	0.7579	0.6090	0.7579	0.8706
No log	65.0	130	0.6912	0.6272	0.6912	0.8314
No log	66.0	132	0.5857	0.6343	0.5857	0.7653
No log	67.0	134	0.5710	0.6430	0.5710	0.7557
No log	68.0	136	0.5887	0.6501	0.5887	0.7672
No log	69.0	138	0.6751	0.6228	0.6751	0.8217
No log	70.0	140	0.6614	0.6290	0.6614	0.8133
No log	71.0	142	0.6584	0.6364	0.6584	0.8114
No log	72.0	144	0.6414	0.6391	0.6414	0.8009
No log	73.0	146	0.6510	0.6382	0.6510	0.8068
No log	74.0	148	0.6966	0.6168	0.6966	0.8346
No log	75.0	150	0.6713	0.6319	0.6713	0.8193

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0