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	6	5.1137	0.0359	5.1137	2.2613
No log	2.0	12	2.2905	0.0740	2.2905	1.5134
No log	3.0	18	1.2367	0.0316	1.2367	1.1121
No log	4.0	24	1.5419	0.0420	1.5419	1.2417
No log	5.0	30	0.7665	0.4161	0.7665	0.8755
No log	6.0	36	1.2404	0.0759	1.2404	1.1137
No log	7.0	42	0.7398	0.4068	0.7398	0.8601
No log	8.0	48	0.5993	0.4426	0.5993	0.7741
No log	9.0	54	0.5047	0.5447	0.5047	0.7104
No log	10.0	60	0.6358	0.4624	0.6358	0.7974
No log	11.0	66	0.6065	0.5382	0.6065	0.7788
No log	12.0	72	0.6350	0.5619	0.6350	0.7969
No log	13.0	78	0.7174	0.4969	0.7174	0.8470
No log	14.0	84	0.7581	0.4746	0.7581	0.8707
No log	15.0	90	0.7582	0.5550	0.7582	0.8707
No log	16.0	96	0.8273	0.5129	0.8273	0.9096
No log	17.0	102	0.6153	0.5334	0.6153	0.7844
No log	18.0	108	1.2710	0.3575	1.2710	1.1274
No log	19.0	114	0.8839	0.3385	0.8839	0.9401
No log	20.0	120	0.5374	0.6402	0.5374	0.7330
No log	21.0	126	1.0281	0.3461	1.0281	1.0140
No log	22.0	132	0.8093	0.4467	0.8093	0.8996
No log	23.0	138	0.5587	0.6189	0.5587	0.7475
No log	24.0	144	0.7769	0.5143	0.7769	0.8814
No log	25.0	150	0.7077	0.5124	0.7077	0.8413
No log	26.0	156	0.8534	0.4738	0.8534	0.9238
No log	27.0	162	0.6841	0.5289	0.6841	0.8271
No log	28.0	168	0.6480	0.5544	0.6480	0.8050
No log	29.0	174	0.8219	0.5031	0.8219	0.9066
No log	30.0	180	0.8935	0.4927	0.8935	0.9452
No log	31.0	186	0.6711	0.5133	0.6711	0.8192
No log	32.0	192	0.6639	0.5506	0.6639	0.8148
No log	33.0	198	0.6259	0.5767	0.6259	0.7911
No log	34.0	204	0.7841	0.5193	0.7841	0.8855
No log	35.0	210	0.5611	0.6133	0.5611	0.7490
No log	36.0	216	0.5873	0.5779	0.5873	0.7663
No log	37.0	222	0.9061	0.5022	0.9061	0.9519
No log	38.0	228	0.8988	0.4995	0.8988	0.9481
No log	39.0	234	0.5765	0.5654	0.5765	0.7593
No log	40.0	240	0.6384	0.5618	0.6384	0.7990

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV6_k3_task1_organization_k3_k3_fold4

Version2ASAP_FineTuningBERT_AugV6_k3_task1_organization_k3_k3_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV6_k3_task1_organization_k3_k3_fold4