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	8.9027	0.0	8.9001	2.9833
No log	2.0	8	6.9885	0.0	6.9862	2.6431
No log	3.0	12	4.9584	0.0045	4.9564	2.2263
No log	4.0	16	3.3346	0.0	3.3327	1.8256
No log	5.0	20	2.2173	-0.0296	2.2156	1.4885
No log	6.0	24	1.9836	0.0283	1.9820	1.4078
No log	7.0	28	1.4034	0.0	1.4019	1.1840
No log	8.0	32	1.3013	0.0106	1.2998	1.1401
No log	9.0	36	1.7489	0.0837	1.7473	1.3218
No log	10.0	40	0.9352	0.0874	0.9339	0.9664
No log	11.0	44	1.6391	0.0798	1.6372	1.2795
No log	12.0	48	1.4201	0.0618	1.4183	1.1909
No log	13.0	52	1.5682	0.0904	1.5666	1.2516
No log	14.0	56	1.1815	0.2111	1.1801	1.0863
No log	15.0	60	0.9484	0.3267	0.9474	0.9733
No log	16.0	64	2.1767	0.0959	2.1750	1.4748
No log	17.0	68	0.9795	0.3432	0.9786	0.9892
No log	18.0	72	1.2152	0.2795	1.2141	1.1019
No log	19.0	76	2.0502	0.1465	2.0487	1.4313
No log	20.0	80	0.7919	0.4072	0.7910	0.8894
No log	21.0	84	1.6080	0.2193	1.6065	1.2675
No log	22.0	88	1.4041	0.2467	1.4027	1.1844
No log	23.0	92	0.8682	0.3413	0.8671	0.9312
No log	24.0	96	1.5421	0.2383	1.5408	1.2413
No log	25.0	100	0.8494	0.4091	0.8486	0.9212
No log	26.0	104	0.9854	0.3315	0.9845	0.9922
No log	27.0	108	1.6138	0.1492	1.6124	1.2698
No log	28.0	112	1.2794	0.1952	1.2783	1.1306
No log	29.0	116	1.5141	0.1717	1.5129	1.2300
No log	30.0	120	1.4073	0.2142	1.4062	1.1858
No log	31.0	124	0.9940	0.3281	0.9932	0.9966
No log	32.0	128	1.3780	0.1877	1.3769	1.1734
No log	33.0	132	1.2211	0.2117	1.2201	1.1046
No log	34.0	136	1.0135	0.3043	1.0127	1.0063
No log	35.0	140	1.5335	0.1637	1.5322	1.2378
No log	36.0	144	1.4578	0.1926	1.4567	1.2069
No log	37.0	148	1.0118	0.3344	1.0109	1.0055
No log	38.0	152	1.0467	0.3258	1.0457	1.0226
No log	39.0	156	1.6390	0.1350	1.6376	1.2797
No log	40.0	160	0.9432	0.3254	0.9424	0.9708
No log	41.0	164	1.2120	0.2504	1.2109	1.1004
No log	42.0	168	1.2609	0.2387	1.2597	1.1224
No log	43.0	172	0.8953	0.3545	0.8944	0.9458
No log	44.0	176	1.4495	0.1923	1.4481	1.2034
No log	45.0	180	1.0918	0.2969	1.0907	1.0444

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV6_k4_task1_organization_k4_k4_fold1

ASAP_FineTuningBERT_AugV6_k4_task1_organization_k4_k4_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k4_task1_organization_k4_k4_fold1