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	6.3936	0.0018	6.3936	2.5286
No log	2.0	12	3.9105	0.0079	3.9105	1.9775
No log	3.0	18	2.2043	0.1268	2.2043	1.4847
No log	4.0	24	1.3036	0.0316	1.3036	1.1418
No log	5.0	30	2.7164	0.0599	2.7164	1.6482
No log	6.0	36	1.1546	0.0621	1.1546	1.0745
No log	7.0	42	1.3604	0.0645	1.3604	1.1663
No log	8.0	48	2.2892	0.2425	2.2892	1.5130
No log	9.0	54	1.3433	0.0927	1.3433	1.1590
No log	10.0	60	1.5851	0.0867	1.5851	1.2590
No log	11.0	66	1.3020	0.1998	1.3020	1.1410
No log	12.0	72	1.4792	0.1973	1.4792	1.2162
No log	13.0	78	0.9547	0.1614	0.9547	0.9771
No log	14.0	84	1.1964	0.2213	1.1964	1.0938
No log	15.0	90	1.1858	0.3788	1.1858	1.0889
No log	16.0	96	0.7393	0.3880	0.7393	0.8598
No log	17.0	102	1.2999	0.3830	1.2999	1.1401
No log	18.0	108	0.5998	0.4388	0.5998	0.7745
No log	19.0	114	0.6679	0.5723	0.6679	0.8173
No log	20.0	120	0.5861	0.5702	0.5861	0.7656
No log	21.0	126	0.8189	0.3463	0.8189	0.9049
No log	22.0	132	0.7743	0.5401	0.7743	0.8800
No log	23.0	138	1.2422	0.4765	1.2422	1.1146
No log	24.0	144	0.6120	0.6251	0.6120	0.7823
No log	25.0	150	0.5761	0.6110	0.5761	0.7590
No log	26.0	156	0.7116	0.5714	0.7116	0.8436
No log	27.0	162	0.6687	0.6310	0.6687	0.8177
No log	28.0	168	0.6075	0.6560	0.6075	0.7794
No log	29.0	174	0.5564	0.6349	0.5564	0.7459
No log	30.0	180	0.6075	0.6349	0.6075	0.7794
No log	31.0	186	0.5764	0.6538	0.5764	0.7592
No log	32.0	192	0.5502	0.6713	0.5502	0.7417
No log	33.0	198	0.6308	0.6402	0.6308	0.7942
No log	34.0	204	0.8136	0.5875	0.8136	0.9020
No log	35.0	210	0.9487	0.5750	0.9487	0.9740
No log	36.0	216	0.6748	0.6480	0.6748	0.8215
No log	37.0	222	0.6993	0.6458	0.6993	0.8362
No log	38.0	228	0.7079	0.6457	0.7079	0.8413
No log	39.0	234	0.7220	0.6060	0.7220	0.8497
No log	40.0	240	0.7941	0.5957	0.7941	0.8911
No log	41.0	246	0.6572	0.6341	0.6572	0.8107
No log	42.0	252	0.6232	0.6265	0.6232	0.7894
No log	43.0	258	0.6816	0.6398	0.6816	0.8256
No log	44.0	264	0.7476	0.6382	0.7476	0.8646
No log	45.0	270	0.6656	0.6541	0.6656	0.8158
No log	46.0	276	0.6855	0.6403	0.6855	0.8279
No log	47.0	282	0.7388	0.6353	0.7388	0.8596
No log	48.0	288	0.9293	0.5853	0.9293	0.9640
No log	49.0	294	0.7640	0.5975	0.7640	0.8741
No log	50.0	300	0.7293	0.6359	0.7293	0.8540
No log	51.0	306	0.8607	0.5968	0.8607	0.9277
No log	52.0	312	0.7016	0.6188	0.7016	0.8376

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_fold4

ASAP_FineTuningBERT_AugV15_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_AugV15_k7_task1_organization_k7_k7_fold4