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	4	9.8591	0.0018	9.8591	3.1399
No log	2.0	8	6.6704	0.0	6.6704	2.5827
No log	3.0	12	4.5417	0.0079	4.5417	2.1311
No log	4.0	16	3.0513	0.0040	3.0513	1.7468
No log	5.0	20	1.9261	0.0775	1.9261	1.3878
No log	6.0	24	1.2095	0.0316	1.2095	1.0998
No log	7.0	28	1.7467	0.1670	1.7467	1.3216
No log	8.0	32	1.3629	0.0975	1.3629	1.1674
No log	9.0	36	0.9848	0.0547	0.9848	0.9924
No log	10.0	40	1.4968	0.1369	1.4968	1.2234
No log	11.0	44	0.7150	0.4518	0.7150	0.8456
No log	12.0	48	1.0526	0.2832	1.0526	1.0260
No log	13.0	52	0.6385	0.4833	0.6385	0.7991
No log	14.0	56	0.9159	0.3700	0.9159	0.9570
No log	15.0	60	0.6088	0.4698	0.6088	0.7802
No log	16.0	64	0.8007	0.4074	0.8007	0.8948
No log	17.0	68	0.7919	0.4581	0.7919	0.8899
No log	18.0	72	0.6640	0.5056	0.6640	0.8149
No log	19.0	76	1.1103	0.3604	1.1103	1.0537
No log	20.0	80	0.7283	0.4667	0.7283	0.8534
No log	21.0	84	0.9478	0.4019	0.9478	0.9735
No log	22.0	88	0.7445	0.5018	0.7445	0.8628
No log	23.0	92	0.7235	0.4776	0.7235	0.8506
No log	24.0	96	0.6912	0.4777	0.6912	0.8314
No log	25.0	100	0.7905	0.4345	0.7905	0.8891
No log	26.0	104	0.9573	0.3684	0.9573	0.9784
No log	27.0	108	0.7260	0.5126	0.7260	0.8521
No log	28.0	112	0.8094	0.4322	0.8094	0.8997
No log	29.0	116	0.7775	0.4316	0.7775	0.8817
No log	30.0	120	0.7391	0.4516	0.7391	0.8597
No log	31.0	124	0.8158	0.4029	0.8158	0.9032
No log	32.0	128	0.7158	0.5216	0.7158	0.8461
No log	33.0	132	0.6976	0.5211	0.6976	0.8352
No log	34.0	136	0.7046	0.5238	0.7046	0.8394
No log	35.0	140	0.6902	0.5198	0.6902	0.8308
No log	36.0	144	0.7425	0.4725	0.7425	0.8617
No log	37.0	148	0.7238	0.4996	0.7238	0.8508
No log	38.0	152	0.6750	0.5281	0.6750	0.8216
No log	39.0	156	0.7239	0.5124	0.7239	0.8508
No log	40.0	160	0.7238	0.4791	0.7238	0.8507
No log	41.0	164	0.7507	0.4221	0.7507	0.8664
No log	42.0	168	0.6914	0.5149	0.6914	0.8315
No log	43.0	172	0.7150	0.4783	0.7150	0.8456
No log	44.0	176	0.6684	0.5053	0.6684	0.8176
No log	45.0	180	0.7009	0.4605	0.7009	0.8372
No log	46.0	184	0.6900	0.4725	0.6900	0.8307
No log	47.0	188	0.6755	0.4938	0.6755	0.8219
No log	48.0	192	0.6810	0.4756	0.6810	0.8252

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV7_k4_task1_organization_k4_k4_fold4

ASAP_FineTuningBERT_AugV7_k4_task1_organization_k4_k4_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV7_k4_task1_organization_k4_k4_fold4