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	8	4.3411	0.0113	4.3411	2.0835
No log	2.0	16	1.6340	0.0470	1.6340	1.2783
No log	3.0	24	1.7111	0.1583	1.7111	1.3081
No log	4.0	32	1.7117	0.2043	1.7117	1.3083
No log	5.0	40	1.4168	0.1752	1.4168	1.1903
No log	6.0	48	0.7040	0.4363	0.7040	0.8390
No log	7.0	56	0.6981	0.4385	0.6981	0.8355
No log	8.0	64	1.1116	0.3877	1.1116	1.0543
No log	9.0	72	0.6533	0.5489	0.6533	0.8083
No log	10.0	80	1.2165	0.3593	1.2165	1.1030
No log	11.0	88	1.1229	0.3676	1.1229	1.0596
No log	12.0	96	0.7932	0.4697	0.7932	0.8906
No log	13.0	104	0.6814	0.5261	0.6814	0.8254
No log	14.0	112	0.7439	0.5048	0.7439	0.8625
No log	15.0	120	0.7863	0.4744	0.7863	0.8868
No log	16.0	128	0.7196	0.5253	0.7196	0.8483
No log	17.0	136	0.9064	0.4072	0.9064	0.9520
No log	18.0	144	0.6992	0.5282	0.6992	0.8362
No log	19.0	152	0.7197	0.5165	0.7197	0.8484
No log	20.0	160	0.7832	0.4364	0.7832	0.8850
No log	21.0	168	0.9691	0.3848	0.9691	0.9844
No log	22.0	176	0.7286	0.4969	0.7286	0.8536
No log	23.0	184	0.9029	0.4337	0.9029	0.9502
No log	24.0	192	0.6238	0.5580	0.6238	0.7898
No log	25.0	200	0.6457	0.5705	0.6457	0.8036
No log	26.0	208	0.8617	0.4253	0.8617	0.9283
No log	27.0	216	0.7226	0.5102	0.7226	0.8500
No log	28.0	224	0.6764	0.5498	0.6764	0.8225
No log	29.0	232	0.7856	0.4513	0.7856	0.8863
No log	30.0	240	0.7676	0.4696	0.7676	0.8761
No log	31.0	248	0.7939	0.4501	0.7939	0.8910
No log	32.0	256	0.9035	0.4100	0.9035	0.9505
No log	33.0	264	1.0364	0.3607	1.0364	1.0180
No log	34.0	272	0.7283	0.5173	0.7283	0.8534
No log	35.0	280	0.6771	0.5311	0.6771	0.8229
No log	36.0	288	0.8155	0.4433	0.8155	0.9030
No log	37.0	296	0.7754	0.4659	0.7754	0.8806
No log	38.0	304	0.9267	0.4091	0.9267	0.9627
No log	39.0	312	0.8542	0.4257	0.8542	0.9242
No log	40.0	320	1.0113	0.3676	1.0113	1.0056
No log	41.0	328	0.8246	0.4399	0.8246	0.9080
No log	42.0	336	0.7306	0.5185	0.7306	0.8547
No log	43.0	344	0.7114	0.5050	0.7114	0.8434
No log	44.0	352	0.7447	0.5124	0.7447	0.8630
No log	45.0	360	0.7027	0.5375	0.7027	0.8383

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV8_k10_task1_organization_k10_k10_fold4

Version2ASAP_FineTuningBERT_AugV8_k10_task1_organization_k10_k10_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV8_k10_task1_organization_k10_k10_fold4