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	8	5.8790	0.0256	5.8790	2.4247
No log	2.0	16	2.6615	0.0	2.6615	1.6314
No log	3.0	24	1.6233	0.0106	1.6233	1.2741
No log	4.0	32	2.3125	0.0780	2.3125	1.5207
No log	5.0	40	1.1665	0.0426	1.1665	1.0800
No log	6.0	48	0.8212	0.3326	0.8212	0.9062
No log	7.0	56	0.6805	0.2306	0.6805	0.8249
No log	8.0	64	0.6762	0.1758	0.6762	0.8223
No log	9.0	72	0.6317	0.2547	0.6317	0.7948
No log	10.0	80	0.5802	0.3522	0.5802	0.7617
No log	11.0	88	0.5424	0.5093	0.5424	0.7365
No log	12.0	96	0.6926	0.4267	0.6926	0.8322
No log	13.0	104	0.5752	0.5199	0.5752	0.7584
No log	14.0	112	0.6369	0.4962	0.6369	0.7981
No log	15.0	120	0.7207	0.4194	0.7207	0.8489
No log	16.0	128	0.6475	0.5199	0.6475	0.8046
No log	17.0	136	0.7391	0.4437	0.7391	0.8597
No log	18.0	144	0.6979	0.5064	0.6979	0.8354
No log	19.0	152	0.6405	0.4954	0.6405	0.8003
No log	20.0	160	0.6371	0.5020	0.6371	0.7982
No log	21.0	168	0.7419	0.5069	0.7419	0.8614
No log	22.0	176	0.7226	0.4619	0.7226	0.8501
No log	23.0	184	0.7019	0.5062	0.7019	0.8378
No log	24.0	192	0.7469	0.4675	0.7469	0.8642
No log	25.0	200	0.8306	0.4788	0.8306	0.9114
No log	26.0	208	0.7187	0.5359	0.7187	0.8478
No log	27.0	216	0.7931	0.4558	0.7931	0.8906
No log	28.0	224	0.7271	0.4964	0.7271	0.8527
No log	29.0	232	0.7559	0.4724	0.7559	0.8694
No log	30.0	240	0.7290	0.5211	0.7290	0.8538
No log	31.0	248	0.7778	0.4511	0.7778	0.8819
No log	32.0	256	0.8273	0.4654	0.8273	0.9096
No log	33.0	264	0.7077	0.5204	0.7077	0.8413
No log	34.0	272	0.7204	0.4801	0.7204	0.8488
No log	35.0	280	0.7845	0.4805	0.7845	0.8857
No log	36.0	288	0.8213	0.4304	0.8213	0.9063
No log	37.0	296	0.7296	0.4958	0.7296	0.8542
No log	38.0	304	0.7761	0.4383	0.7761	0.8810
No log	39.0	312	0.7965	0.4713	0.7965	0.8924
No log	40.0	320	0.8579	0.4354	0.8579	0.9262
No log	41.0	328	0.7365	0.4708	0.7365	0.8582
No log	42.0	336	0.7380	0.4443	0.7380	0.8591
No log	43.0	344	0.7346	0.4295	0.7346	0.8571
No log	44.0	352	0.7806	0.4685	0.7806	0.8835
No log	45.0	360	0.8028	0.4497	0.8028	0.8960
No log	46.0	368	0.7549	0.4783	0.7549	0.8688

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_nosemantic_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0

ASAP_nosemantic_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_nosemantic_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0