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	4	8.8226	0.0018	8.8226	2.9703
No log	2.0	8	6.1964	0.0018	6.1964	2.4893
No log	3.0	12	4.4591	0.0079	4.4591	2.1117
No log	4.0	16	3.1213	0.0040	3.1213	1.7667
No log	5.0	20	2.1451	0.0457	2.1451	1.4646
No log	6.0	24	1.4739	0.0316	1.4739	1.2140
No log	7.0	28	1.0190	0.0316	1.0190	1.0095
No log	8.0	32	0.7832	0.3704	0.7832	0.8850
No log	9.0	36	1.2221	0.2443	1.2221	1.1055
No log	10.0	40	0.7135	0.5014	0.7135	0.8447
No log	11.0	44	0.8687	0.4420	0.8687	0.9320
No log	12.0	48	0.6526	0.4206	0.6526	0.8078
No log	13.0	52	0.6704	0.5200	0.6704	0.8188
No log	14.0	56	0.6909	0.4524	0.6909	0.8312
No log	15.0	60	0.9409	0.4293	0.9409	0.9700
No log	16.0	64	0.5975	0.5360	0.5975	0.7730
No log	17.0	68	0.6007	0.6028	0.6007	0.7751
No log	18.0	72	0.5876	0.6253	0.5876	0.7665
No log	19.0	76	0.6713	0.6129	0.6713	0.8193
No log	20.0	80	0.5981	0.6278	0.5981	0.7734
No log	21.0	84	0.7242	0.5728	0.7242	0.8510
No log	22.0	88	0.5642	0.6306	0.5642	0.7511
No log	23.0	92	0.5905	0.6098	0.5905	0.7684
No log	24.0	96	0.5795	0.5891	0.5795	0.7613
No log	25.0	100	0.5587	0.6044	0.5587	0.7475
No log	26.0	104	0.5861	0.5927	0.5861	0.7656
No log	27.0	108	0.6044	0.5803	0.6044	0.7774
No log	28.0	112	0.5848	0.5838	0.5848	0.7647
No log	29.0	116	0.5617	0.6036	0.5617	0.7495
No log	30.0	120	0.5569	0.6090	0.5569	0.7462
No log	31.0	124	0.5599	0.6204	0.5599	0.7483
No log	32.0	128	0.5798	0.6007	0.5798	0.7614
No log	33.0	132	0.5808	0.6077	0.5808	0.7621
No log	34.0	136	0.5676	0.6054	0.5676	0.7534
No log	35.0	140	0.5550	0.6051	0.5550	0.7450
No log	36.0	144	0.5744	0.6079	0.5744	0.7579
No log	37.0	148	0.5638	0.6166	0.5638	0.7509
No log	38.0	152	0.5511	0.6061	0.5511	0.7424
No log	39.0	156	0.5467	0.6043	0.5467	0.7394
No log	40.0	160	0.5592	0.6141	0.5592	0.7478
No log	41.0	164	0.6142	0.6224	0.6142	0.7837
No log	42.0	168	0.5883	0.5928	0.5883	0.7670

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold4

ASAP_nosemantic_FineTuningBERT_AugV12_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_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold4