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	8.3384	0.0018	8.3384	2.8876
No log	2.0	12	3.3031	0.0079	3.3031	1.8174
No log	3.0	18	1.3495	0.0316	1.3495	1.1617
No log	4.0	24	1.0787	0.0213	1.0787	1.0386
No log	5.0	30	1.5343	0.0658	1.5343	1.2387
No log	6.0	36	1.6271	0.1416	1.6271	1.2756
No log	7.0	42	1.5497	0.0710	1.5497	1.2449
No log	8.0	48	0.9393	0.1931	0.9393	0.9692
No log	9.0	54	0.6925	0.4384	0.6925	0.8322
No log	10.0	60	0.9314	0.3507	0.9314	0.9651
No log	11.0	66	0.6102	0.4244	0.6102	0.7812
No log	12.0	72	0.6243	0.4163	0.6243	0.7901
No log	13.0	78	0.7443	0.3968	0.7443	0.8627
No log	14.0	84	0.7662	0.4081	0.7662	0.8754
No log	15.0	90	0.8070	0.3656	0.8070	0.8983
No log	16.0	96	0.7472	0.4440	0.7472	0.8644
No log	17.0	102	0.6224	0.4993	0.6224	0.7889
No log	18.0	108	0.6704	0.4620	0.6704	0.8188
No log	19.0	114	0.6284	0.4741	0.6284	0.7927
No log	20.0	120	0.6247	0.4791	0.6247	0.7904
No log	21.0	126	0.6226	0.5030	0.6226	0.7891
No log	22.0	132	0.6299	0.5152	0.6299	0.7937
No log	23.0	138	0.6393	0.5039	0.6393	0.7996
No log	24.0	144	0.6274	0.5064	0.6274	0.7921
No log	25.0	150	0.7846	0.5172	0.7846	0.8858
No log	26.0	156	0.7875	0.4185	0.7875	0.8874
No log	27.0	162	0.8600	0.4234	0.8600	0.9274
No log	28.0	168	0.7460	0.4764	0.7460	0.8637
No log	29.0	174	0.7935	0.4501	0.7935	0.8908
No log	30.0	180	0.7412	0.4403	0.7412	0.8609
No log	31.0	186	0.7200	0.4291	0.7200	0.8485
No log	32.0	192	0.6343	0.5024	0.6343	0.7964
No log	33.0	198	0.6312	0.4774	0.6312	0.7945
No log	34.0	204	0.6474	0.4743	0.6474	0.8046
No log	35.0	210	0.6161	0.5026	0.6161	0.7849
No log	36.0	216	0.6478	0.4750	0.6478	0.8049
No log	37.0	222	0.7033	0.4637	0.7033	0.8386
No log	38.0	228	0.6957	0.4670	0.6957	0.8341
No log	39.0	234	0.6798	0.4521	0.6798	0.8245
No log	40.0	240	0.7189	0.4173	0.7189	0.8479
No log	41.0	246	0.7334	0.4550	0.7334	0.8564
No log	42.0	252	0.7055	0.4535	0.7055	0.8399
No log	43.0	258	0.7141	0.4573	0.7141	0.8450
No log	44.0	264	0.6607	0.4524	0.6607	0.8128
No log	45.0	270	0.6678	0.4440	0.6678	0.8172

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold4

ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold4