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	3	11.3372	-0.0035	11.3372	3.3671
No log	2.0	6	9.4140	0.0	9.4140	3.0682
No log	3.0	9	8.3440	0.0	8.3440	2.8886
No log	4.0	12	8.0158	0.0	8.0158	2.8312
No log	5.0	15	7.5228	0.0	7.5228	2.7428
No log	6.0	18	6.0219	0.0454	6.0218	2.4539
No log	7.0	21	4.8272	0.0	4.8272	2.1971
No log	8.0	24	3.1829	0.0	3.1829	1.7841
No log	9.0	27	2.5057	0.1568	2.5057	1.5829
No log	10.0	30	1.6200	0.0	1.6200	1.2728
No log	11.0	33	1.2694	0.0	1.2694	1.1267
No log	12.0	36	1.0894	0.2909	1.0894	1.0437
No log	13.0	39	1.0053	0.2000	1.0053	1.0026
No log	14.0	42	1.0246	0.1317	1.0246	1.0122
No log	15.0	45	0.8647	0.2576	0.8647	0.9299
No log	16.0	48	0.9990	0.4751	0.9990	0.9995
No log	17.0	51	0.8835	0.4557	0.8835	0.9399
No log	18.0	54	0.9943	0.5119	0.9943	0.9971
No log	19.0	57	0.9301	0.5597	0.9301	0.9644
No log	20.0	60	1.0492	0.5923	1.0492	1.0243
No log	21.0	63	1.1641	0.5605	1.1641	1.0789
No log	22.0	66	0.9552	0.5671	0.9552	0.9773
No log	23.0	69	0.9755	0.6104	0.9755	0.9877
No log	24.0	72	0.8604	0.5743	0.8604	0.9276
No log	25.0	75	0.8234	0.6341	0.8234	0.9074
No log	26.0	78	0.7309	0.6810	0.7309	0.8549
No log	27.0	81	0.9928	0.6019	0.9928	0.9964
No log	28.0	84	0.7749	0.6349	0.7749	0.8803
No log	29.0	87	0.9560	0.5872	0.9560	0.9778
No log	30.0	90	0.8218	0.6000	0.8218	0.9065
No log	31.0	93	0.8927	0.6293	0.8927	0.9448
No log	32.0	96	0.9657	0.5819	0.9657	0.9827
No log	33.0	99	0.7484	0.5819	0.7484	0.8651
No log	34.0	102	1.0333	0.5897	1.0333	1.0165
No log	35.0	105	0.7985	0.6300	0.7985	0.8936
No log	36.0	108	0.7495	0.6383	0.7495	0.8658
No log	37.0	111	0.7161	0.6464	0.7161	0.8462
No log	38.0	114	0.6644	0.6657	0.6644	0.8151
No log	39.0	117	0.7487	0.6296	0.7487	0.8653
No log	40.0	120	0.6903	0.6848	0.6903	0.8309
No log	41.0	123	0.7856	0.6471	0.7856	0.8863
No log	42.0	126	0.6984	0.6684	0.6984	0.8357
No log	43.0	129	0.7906	0.6405	0.7906	0.8892
No log	44.0	132	0.7215	0.6227	0.7215	0.8494
No log	45.0	135	0.7534	0.6335	0.7534	0.8680
No log	46.0	138	0.7408	0.6378	0.7408	0.8607
No log	47.0	141	0.7652	0.6519	0.7652	0.8747
No log	48.0	144	0.7117	0.6667	0.7117	0.8436
No log	49.0	147	0.7876	0.6519	0.7876	0.8874
No log	50.0	150	0.6752	0.6529	0.6752	0.8217
No log	51.0	153	0.8198	0.6292	0.8198	0.9054
No log	52.0	156	0.7547	0.6452	0.7547	0.8687
No log	53.0	159	0.6940	0.6471	0.6940	0.8330
No log	54.0	162	0.7334	0.6413	0.7334	0.8564
No log	55.0	165	0.6798	0.6517	0.6798	0.8245
No log	56.0	168	0.7077	0.6313	0.7077	0.8412
No log	57.0	171	0.7590	0.6344	0.7590	0.8712
No log	58.0	174	0.6825	0.6573	0.6825	0.8261
No log	59.0	177	0.6917	0.6573	0.6917	0.8317
No log	60.0	180	0.7646	0.6316	0.7646	0.8744

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2

Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2