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	3	8.1805	0.0	8.1805	2.8602
No log	2.0	6	6.8586	0.0	6.8586	2.6189
No log	3.0	9	5.5652	0.0109	5.5652	2.3591
No log	4.0	12	4.3349	0.0039	4.3349	2.0820
No log	5.0	15	3.1672	0.0	3.1672	1.7797
No log	6.0	18	2.1836	0.0909	2.1836	1.4777
No log	7.0	21	1.5083	0.0316	1.5083	1.2281
No log	8.0	24	1.4276	0.0382	1.4276	1.1948
No log	9.0	27	1.9968	0.1851	1.9968	1.4131
No log	10.0	30	0.9161	0.0316	0.9161	0.9571
No log	11.0	33	1.2578	0.0664	1.2578	1.1215
No log	12.0	36	1.5782	0.1286	1.5782	1.2563
No log	13.0	39	0.9478	0.2671	0.9478	0.9735
No log	14.0	42	1.3597	0.2083	1.3597	1.1661
No log	15.0	45	0.9502	0.2560	0.9502	0.9748
No log	16.0	48	0.9796	0.2004	0.9796	0.9898
No log	17.0	51	0.8676	0.2146	0.8676	0.9314
No log	18.0	54	1.0735	0.2459	1.0735	1.0361
No log	19.0	57	1.0725	0.2680	1.0725	1.0356
No log	20.0	60	1.1640	0.2553	1.1640	1.0789
No log	21.0	63	1.1175	0.3166	1.1175	1.0571
No log	22.0	66	1.0434	0.3287	1.0434	1.0214
No log	23.0	69	1.3683	0.2561	1.3683	1.1698
No log	24.0	72	1.0462	0.3456	1.0462	1.0228
No log	25.0	75	1.2361	0.3010	1.2361	1.1118
No log	26.0	78	1.2787	0.2767	1.2787	1.1308
No log	27.0	81	0.9354	0.3732	0.9354	0.9672
No log	28.0	84	1.0475	0.3297	1.0475	1.0235
No log	29.0	87	1.0700	0.3349	1.0700	1.0344
No log	30.0	90	1.0471	0.3671	1.0471	1.0233
No log	31.0	93	0.9059	0.3875	0.9059	0.9518
No log	32.0	96	0.9155	0.3987	0.9155	0.9568
No log	33.0	99	1.0406	0.3351	1.0406	1.0201
No log	34.0	102	1.0586	0.3419	1.0586	1.0289
No log	35.0	105	0.9328	0.3671	0.9328	0.9658
No log	36.0	108	1.0620	0.3195	1.0620	1.0305
No log	37.0	111	0.8858	0.4056	0.8858	0.9412
No log	38.0	114	0.9671	0.3573	0.9671	0.9834
No log	39.0	117	0.8910	0.4047	0.8910	0.9439
No log	40.0	120	0.9231	0.3802	0.9231	0.9608
No log	41.0	123	0.8919	0.3671	0.8919	0.9444
No log	42.0	126	0.8773	0.3967	0.8773	0.9366
No log	43.0	129	1.0095	0.3678	1.0095	1.0047
No log	44.0	132	0.9305	0.3825	0.9305	0.9646
No log	45.0	135	0.9924	0.3405	0.9924	0.9962
No log	46.0	138	0.8906	0.3821	0.8906	0.9437
No log	47.0	141	0.9059	0.3697	0.9059	0.9518
No log	48.0	144	0.8986	0.3812	0.8986	0.9479
No log	49.0	147	0.9296	0.3538	0.9296	0.9641
No log	50.0	150	0.8854	0.3468	0.8854	0.9409
No log	51.0	153	0.8065	0.4068	0.8065	0.8981
No log	52.0	156	0.9167	0.3453	0.9167	0.9574
No log	53.0	159	0.8745	0.4100	0.8745	0.9351
No log	54.0	162	0.8866	0.4013	0.8866	0.9416
No log	55.0	165	1.0591	0.3441	1.0591	1.0291
No log	56.0	168	0.8870	0.3494	0.8870	0.9418
No log	57.0	171	0.8441	0.4329	0.8441	0.9187
No log	58.0	174	0.8822	0.3639	0.8822	0.9393
No log	59.0	177	0.8777	0.3789	0.8777	0.9369
No log	60.0	180	0.8422	0.3919	0.8422	0.9177
No log	61.0	183	0.9169	0.3726	0.9169	0.9575
No log	62.0	186	0.8986	0.3794	0.8986	0.9479
No log	63.0	189	0.8423	0.3873	0.8423	0.9178
No log	64.0	192	0.8412	0.3930	0.8412	0.9172
No log	65.0	195	0.9234	0.3578	0.9234	0.9610
No log	66.0	198	0.9026	0.3815	0.9026	0.9501
No log	67.0	201	0.9072	0.3684	0.9072	0.9525
No log	68.0	204	0.9672	0.3360	0.9672	0.9835
No log	69.0	207	0.9092	0.3718	0.9092	0.9535
No log	70.0	210	0.9131	0.3737	0.9131	0.9555
No log	71.0	213	0.9630	0.3369	0.9630	0.9813
No log	72.0	216	0.9287	0.3715	0.9287	0.9637
No log	73.0	219	0.9398	0.3468	0.9398	0.9694
No log	74.0	222	0.8649	0.3698	0.8649	0.9300
No log	75.0	225	0.8769	0.3580	0.8769	0.9365
No log	76.0	228	0.9409	0.3515	0.9409	0.9700
No log	77.0	231	0.9204	0.3579	0.9204	0.9594

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold0

ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold0