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	11.0276	0.0227	11.0274	3.3208
No log	2.0	6	7.7111	0.0	7.7113	2.7769
No log	3.0	9	4.8793	0.0387	4.8797	2.2090
No log	4.0	12	3.2944	0.0	3.2949	1.8152
No log	5.0	15	2.1118	0.1453	2.1123	1.4534
No log	6.0	18	1.5181	0.0345	1.5185	1.2323
No log	7.0	21	1.0615	0.0213	1.0619	1.0305
No log	8.0	24	1.0678	0.0449	1.0681	1.0335
No log	9.0	27	0.8735	0.2122	0.8738	0.9348
No log	10.0	30	0.7716	0.4039	0.7718	0.8785
No log	11.0	33	1.3435	0.1991	1.3437	1.1592
No log	12.0	36	0.8524	0.3504	0.8526	0.9234
No log	13.0	39	0.6318	0.5126	0.6319	0.7949
No log	14.0	42	0.7239	0.3945	0.7240	0.8509
No log	15.0	45	0.6376	0.4734	0.6377	0.7985
No log	16.0	48	0.5572	0.4675	0.5570	0.7463
No log	17.0	51	0.8917	0.3204	0.8917	0.9443
No log	18.0	54	0.6061	0.4863	0.6060	0.7784
No log	19.0	57	0.6273	0.4854	0.6270	0.7919
No log	20.0	60	1.0581	0.3048	1.0581	1.0286
No log	21.0	63	0.5286	0.5059	0.5283	0.7269
No log	22.0	66	0.5711	0.4999	0.5709	0.7556
No log	23.0	69	0.5744	0.5327	0.5740	0.7576
No log	24.0	72	0.5887	0.5236	0.5881	0.7669
No log	25.0	75	0.8011	0.4363	0.8007	0.8948
No log	26.0	78	0.5879	0.5414	0.5873	0.7664
No log	27.0	81	1.1357	0.3111	1.1354	1.0656
No log	28.0	84	0.6107	0.5316	0.6102	0.7812
No log	29.0	87	1.0239	0.2999	1.0236	1.0117
No log	30.0	90	0.6212	0.4752	0.6207	0.7878
No log	31.0	93	1.2577	0.2451	1.2574	1.1214
No log	32.0	96	1.0828	0.2757	1.0825	1.0404
No log	33.0	99	0.6097	0.4637	0.6091	0.7804
No log	34.0	102	1.0679	0.3219	1.0675	1.0332
No log	35.0	105	0.6300	0.4578	0.6295	0.7934
No log	36.0	108	0.9080	0.3548	0.9077	0.9527
No log	37.0	111	0.5697	0.5288	0.5691	0.7544
No log	38.0	114	0.8891	0.3748	0.8887	0.9427
No log	39.0	117	0.5985	0.5010	0.5980	0.7733
No log	40.0	120	1.0470	0.3174	1.0466	1.0230
No log	41.0	123	0.5649	0.5457	0.5643	0.7512
No log	42.0	126	0.5899	0.5038	0.5892	0.7676
No log	43.0	129	1.1410	0.2807	1.1407	1.0680
No log	44.0	132	0.5758	0.5110	0.5752	0.7584
No log	45.0	135	0.5913	0.4789	0.5908	0.7686
No log	46.0	138	0.9774	0.3372	0.9771	0.9885
No log	47.0	141	0.5528	0.5167	0.5523	0.7432
No log	48.0	144	0.7719	0.3966	0.7716	0.8784
No log	49.0	147	0.7221	0.4288	0.7217	0.8495
No log	50.0	150	0.7135	0.4336	0.7131	0.8444
No log	51.0	153	0.7223	0.4321	0.7217	0.8495
No log	52.0	156	0.8440	0.3741	0.8435	0.9184
No log	53.0	159	0.6700	0.4288	0.6696	0.8183
No log	54.0	162	0.6713	0.4293	0.6709	0.8191
No log	55.0	165	0.7718	0.3989	0.7715	0.8783
No log	56.0	168	0.6479	0.4517	0.6474	0.8046

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial2BERT_AugV8_k3_task1_organization_sp010_lw040_fold2

Trial2BERT_AugV8_k3_task1_organization_sp010_lw040_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial2BERT_AugV8_k3_task1_organization_sp010_lw040_fold2