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	8.3184	0.0	8.3156	2.8837
No log	2.0	6	6.2079	0.0	6.2055	2.4911
No log	3.0	9	4.4246	0.0040	4.4224	2.1030
No log	4.0	12	3.0883	0.0	3.0865	1.7568
No log	5.0	15	2.1064	0.1289	2.1045	1.4507
No log	6.0	18	1.5711	0.0106	1.5696	1.2528
No log	7.0	21	1.1998	0.0106	1.1982	1.0946
No log	8.0	24	1.1787	0.0106	1.1773	1.0851
No log	9.0	27	1.2951	0.0872	1.2935	1.1373
No log	10.0	30	0.8698	0.2440	0.8683	0.9318
No log	11.0	33	0.8398	0.1565	0.8386	0.9157
No log	12.0	36	1.0060	0.1841	1.0047	1.0023
No log	13.0	39	0.9420	0.1764	0.9409	0.9700
No log	14.0	42	0.9039	0.3769	0.9028	0.9502
No log	15.0	45	0.7328	0.4489	0.7314	0.8552
No log	16.0	48	0.7690	0.4152	0.7676	0.8761
No log	17.0	51	0.9804	0.3450	0.9794	0.9896
No log	18.0	54	0.7155	0.4532	0.7148	0.8455
No log	19.0	57	0.8336	0.4476	0.8331	0.9128
No log	20.0	60	0.7521	0.4754	0.7515	0.8669
No log	21.0	63	0.8095	0.4540	0.8086	0.8992
No log	22.0	66	0.6595	0.5241	0.6587	0.8116
No log	23.0	69	1.0324	0.3849	1.0316	1.0157
No log	24.0	72	0.7184	0.5166	0.7179	0.8473
No log	25.0	75	1.1182	0.3588	1.1173	1.0570
No log	26.0	78	0.6798	0.5497	0.6794	0.8242
No log	27.0	81	0.7472	0.5046	0.7467	0.8641
No log	28.0	84	0.7986	0.4622	0.7982	0.8934
No log	29.0	87	0.7647	0.4443	0.7642	0.8742
No log	30.0	90	0.6819	0.5224	0.6816	0.8256
No log	31.0	93	0.9976	0.4019	0.9970	0.9985
No log	32.0	96	0.7076	0.5144	0.7075	0.8411
No log	33.0	99	0.8219	0.4414	0.8217	0.9065
No log	34.0	102	0.7522	0.4787	0.7520	0.8672
No log	35.0	105	0.8480	0.4401	0.8476	0.9207
No log	36.0	108	0.7596	0.4852	0.7592	0.8713
No log	37.0	111	0.7949	0.4672	0.7944	0.8913
No log	38.0	114	0.7213	0.4657	0.7208	0.8490
No log	39.0	117	0.6800	0.5037	0.6797	0.8244
No log	40.0	120	0.7591	0.4810	0.7589	0.8711
No log	41.0	123	0.7510	0.4875	0.7510	0.8666
No log	42.0	126	0.7685	0.4546	0.7684	0.8766
No log	43.0	129	0.6517	0.5194	0.6517	0.8073
No log	44.0	132	0.7555	0.4796	0.7553	0.8691
No log	45.0	135	0.6828	0.5327	0.6827	0.8262
No log	46.0	138	0.7586	0.5107	0.7584	0.8708

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold1

ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold1