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	10.6066	0.0016	10.6069	3.2568
No log	2.0	6	7.5763	0.0	7.5765	2.7525
No log	3.0	9	5.1435	0.0102	5.1439	2.2680
No log	4.0	12	3.5862	0.0039	3.5867	1.8939
No log	5.0	15	2.6036	0.0	2.6040	1.6137
No log	6.0	18	1.8001	0.0280	1.8006	1.3419
No log	7.0	21	1.3209	0.0107	1.3213	1.1495
No log	8.0	24	1.0312	0.0280	1.0316	1.0157
No log	9.0	27	0.7918	0.2443	0.7921	0.8900
No log	10.0	30	0.7129	0.4930	0.7132	0.8445
No log	11.0	33	0.7638	0.4810	0.7641	0.8741
No log	12.0	36	1.0266	0.3629	1.0271	1.0135
No log	13.0	39	0.5535	0.4878	0.5537	0.7441
No log	14.0	42	0.8089	0.4274	0.8094	0.8997
No log	15.0	45	0.5830	0.4349	0.5830	0.7636
No log	16.0	48	0.6641	0.4596	0.6642	0.8150
No log	17.0	51	0.6606	0.4374	0.6605	0.8127
No log	18.0	54	0.7024	0.4983	0.7024	0.8381
No log	19.0	57	0.6453	0.5422	0.6453	0.8033
No log	20.0	60	0.6327	0.5403	0.6326	0.7954
No log	21.0	63	0.6787	0.5547	0.6785	0.8237
No log	22.0	66	0.7376	0.5454	0.7374	0.8587
No log	23.0	69	0.8218	0.5079	0.8215	0.9064
No log	24.0	72	0.9199	0.4938	0.9196	0.9590
No log	25.0	75	0.8575	0.4828	0.8577	0.9261
No log	26.0	78	1.0556	0.4711	1.0553	1.0273
No log	27.0	81	0.8256	0.4599	0.8258	0.9087
No log	28.0	84	0.7107	0.5536	0.7106	0.8430
No log	29.0	87	0.7046	0.5499	0.7046	0.8394
No log	30.0	90	0.7021	0.5509	0.7019	0.8378
No log	31.0	93	0.7461	0.4734	0.7460	0.8637
No log	32.0	96	0.6463	0.5044	0.6462	0.8039
No log	33.0	99	0.6914	0.4813	0.6913	0.8314
No log	34.0	102	0.6989	0.5305	0.6987	0.8359
No log	35.0	105	0.7933	0.4757	0.7935	0.8908
No log	36.0	108	0.6629	0.5436	0.6628	0.8142
No log	37.0	111	0.7277	0.5421	0.7274	0.8529
No log	38.0	114	0.6667	0.5240	0.6666	0.8165
No log	39.0	117	0.6165	0.5301	0.6164	0.7851
No log	40.0	120	0.6427	0.5227	0.6426	0.8016
No log	41.0	123	0.6860	0.5076	0.6859	0.8282

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold2

Version2ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold2