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	8.3679	0.0054	8.3679	2.8927
No log	2.0	6	6.2649	0.0189	6.2649	2.5030
No log	3.0	9	4.5183	0.0126	4.5183	2.1256
No log	4.0	12	3.6468	0.0115	3.6468	1.9097
No log	5.0	15	2.0701	0.1210	2.0701	1.4388
No log	6.0	18	1.5400	0.0562	1.5400	1.2410
No log	7.0	21	1.1963	0.0382	1.1963	1.0937
No log	8.0	24	1.4231	0.0570	1.4231	1.1929
No log	9.0	27	0.9795	0.0635	0.9795	0.9897
No log	10.0	30	0.9616	0.0987	0.9616	0.9806
No log	11.0	33	1.5236	0.0735	1.5236	1.2343
No log	12.0	36	1.2271	0.2019	1.2271	1.1077
No log	13.0	39	1.0761	0.2416	1.0761	1.0373
No log	14.0	42	1.1935	0.0612	1.1935	1.0925
No log	15.0	45	0.7530	0.2849	0.7530	0.8678
No log	16.0	48	1.0130	0.1293	1.0130	1.0065
No log	17.0	51	0.8722	0.2109	0.8722	0.9339
No log	18.0	54	0.9186	0.2789	0.9186	0.9585
No log	19.0	57	1.1033	0.1883	1.1033	1.0504
No log	20.0	60	0.8615	0.3452	0.8615	0.9282
No log	21.0	63	0.9260	0.3151	0.9260	0.9623
No log	22.0	66	0.9071	0.3237	0.9071	0.9524
No log	23.0	69	1.2151	0.1558	1.2151	1.1023
No log	24.0	72	0.8644	0.3290	0.8644	0.9297
No log	25.0	75	1.1547	0.1738	1.1547	1.0746
No log	26.0	78	0.8731	0.3168	0.8731	0.9344
No log	27.0	81	1.2486	0.1820	1.2486	1.1174
No log	28.0	84	0.8258	0.3772	0.8258	0.9087
No log	29.0	87	0.8857	0.2953	0.8857	0.9411
No log	30.0	90	1.0308	0.2512	1.0308	1.0153
No log	31.0	93	0.8741	0.3609	0.8741	0.9350
No log	32.0	96	0.9075	0.3274	0.9075	0.9527
No log	33.0	99	0.9820	0.2590	0.9820	0.9909
No log	34.0	102	0.9038	0.3117	0.9038	0.9507
No log	35.0	105	1.0634	0.2216	1.0634	1.0312
No log	36.0	108	0.8712	0.3437	0.8712	0.9334
No log	37.0	111	1.1273	0.1750	1.1273	1.0618
No log	38.0	114	0.8467	0.3757	0.8467	0.9201
No log	39.0	117	0.8727	0.3619	0.8727	0.9342
No log	40.0	120	1.0911	0.1803	1.0911	1.0446
No log	41.0	123	0.9658	0.2160	0.9658	0.9828
No log	42.0	126	1.0394	0.2407	1.0394	1.0195
No log	43.0	129	0.7829	0.4336	0.7829	0.8848
No log	44.0	132	0.9911	0.2803	0.9911	0.9955
No log	45.0	135	0.9511	0.2749	0.9511	0.9752
No log	46.0	138	1.1503	0.1505	1.1503	1.0725
No log	47.0	141	0.9104	0.2802	0.9104	0.9541
No log	48.0	144	1.0224	0.2245	1.0224	1.0111
No log	49.0	147	0.8449	0.3251	0.8449	0.9192
No log	50.0	150	1.0436	0.2041	1.0436	1.0216
No log	51.0	153	0.8255	0.3260	0.8255	0.9086
No log	52.0	156	0.8464	0.3127	0.8464	0.9200
No log	53.0	159	1.0456	0.2104	1.0456	1.0225
No log	54.0	162	0.8120	0.3407	0.8120	0.9011
No log	55.0	165	1.0304	0.2539	1.0304	1.0151
No log	56.0	168	0.8855	0.3062	0.8855	0.9410
No log	57.0	171	0.7528	0.3691	0.7528	0.8676
No log	58.0	174	1.1068	0.2095	1.1068	1.0520

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/BERT_AugV8_k3_task1_organization_sp010_lw060_fold0

BERT_AugV8_k3_task1_organization_sp010_lw060_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k3_task1_organization_sp010_lw060_fold0