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	3	9.6360	0.0018	9.6360	3.1042
No log	2.0	6	8.4304	0.0	8.4304	2.9035
No log	3.0	9	6.3591	0.0	6.3591	2.5217
No log	4.0	12	4.4965	0.0079	4.4965	2.1205
No log	5.0	15	3.1874	0.0040	3.1874	1.7853
No log	6.0	18	2.3372	0.1127	2.3372	1.5288
No log	7.0	21	1.6036	0.0420	1.6036	1.2663
No log	8.0	24	1.1536	0.0213	1.1536	1.0741
No log	9.0	27	1.0023	0.0213	1.0023	1.0012
No log	10.0	30	0.8369	0.2273	0.8369	0.9148
No log	11.0	33	0.7270	0.4801	0.7270	0.8526
No log	12.0	36	0.9992	0.1742	0.9992	0.9996
No log	13.0	39	0.6398	0.5087	0.6398	0.7999
No log	14.0	42	0.5760	0.5424	0.5760	0.7590
No log	15.0	45	0.5706	0.5609	0.5706	0.7554
No log	16.0	48	0.6032	0.5240	0.6032	0.7766
No log	17.0	51	0.6719	0.5500	0.6719	0.8197
No log	18.0	54	0.5630	0.5771	0.5630	0.7503
No log	19.0	57	0.6625	0.5490	0.6625	0.8140
No log	20.0	60	0.4997	0.6106	0.4997	0.7069
No log	21.0	63	0.5133	0.6374	0.5133	0.7164
No log	22.0	66	0.5437	0.6498	0.5437	0.7374
No log	23.0	69	0.5636	0.6457	0.5636	0.7507
No log	24.0	72	0.5952	0.6162	0.5952	0.7715
No log	25.0	75	0.5611	0.6194	0.5611	0.7491
No log	26.0	78	1.1395	0.4798	1.1395	1.0675
No log	27.0	81	0.8536	0.5826	0.8536	0.9239
No log	28.0	84	0.7131	0.6079	0.7131	0.8444
No log	29.0	87	0.7745	0.5863	0.7745	0.8801
No log	30.0	90	0.5993	0.6152	0.5993	0.7741
No log	31.0	93	0.6077	0.5858	0.6077	0.7795
No log	32.0	96	0.6665	0.5775	0.6665	0.8164
No log	33.0	99	0.7313	0.5795	0.7313	0.8552
No log	34.0	102	0.7916	0.5822	0.7916	0.8897
No log	35.0	105	0.7110	0.5773	0.7110	0.8432
No log	36.0	108	0.6886	0.5967	0.6886	0.8298
No log	37.0	111	0.7416	0.5792	0.7416	0.8612
No log	38.0	114	0.8132	0.5724	0.8132	0.9018
No log	39.0	117	0.9591	0.5467	0.9591	0.9793
No log	40.0	120	0.6688	0.5958	0.6688	0.8178
No log	41.0	123	0.6899	0.6010	0.6899	0.8306
No log	42.0	126	0.7840	0.5773	0.7840	0.8855
No log	43.0	129	0.8726	0.5464	0.8726	0.9341
No log	44.0	132	0.7480	0.5822	0.7480	0.8649
No log	45.0	135	1.1447	0.5078	1.1447	1.0699
No log	46.0	138	0.7831	0.5610	0.7831	0.8850
No log	47.0	141	0.9394	0.5395	0.9394	0.9692
No log	48.0	144	0.6493	0.6082	0.6493	0.8058
No log	49.0	147	0.8654	0.5481	0.8654	0.9303
No log	50.0	150	0.7110	0.5835	0.7110	0.8432
No log	51.0	153	0.5981	0.5749	0.5981	0.7734
No log	52.0	156	0.7143	0.5589	0.7143	0.8452

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version25NewTestASAP_FineTuningBERT_AugV25_k3_task1_organization_k3_k3_fold4

Version25NewTestASAP_FineTuningBERT_AugV25_k3_task1_organization_k3_k3_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version25NewTestASAP_FineTuningBERT_AugV25_k3_task1_organization_k3_k3_fold4