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	10.6913	0.0062	10.6915	3.2698
No log	2.0	6	7.9874	0.0	7.9878	2.8263
No log	3.0	9	5.1986	0.0189	5.1990	2.2801
No log	4.0	12	3.4230	0.0	3.4235	1.8503
No log	5.0	15	2.2353	0.1012	2.2359	1.4953
No log	6.0	18	1.4853	0.0136	1.4858	1.2189
No log	7.0	21	1.0963	0.0	1.0968	1.0473
No log	8.0	24	1.1777	0.0	1.1783	1.0855
No log	9.0	27	1.2012	0.0107	1.2018	1.0963
No log	10.0	30	1.4848	0.0268	1.4854	1.2188
No log	11.0	33	1.0459	0.0280	1.0464	1.0229
No log	12.0	36	1.3049	0.0702	1.3054	1.1425
No log	13.0	39	1.4088	0.0925	1.4091	1.1871
No log	14.0	42	1.1887	0.1426	1.1889	1.0904
No log	15.0	45	1.4061	0.1192	1.4061	1.1858
No log	16.0	48	1.0833	0.2379	1.0831	1.0407
No log	17.0	51	1.9159	0.1242	1.9160	1.3842
No log	18.0	54	0.8622	0.3371	0.8622	0.9286
No log	19.0	57	1.0151	0.3289	1.0153	1.0076
No log	20.0	60	1.3094	0.2917	1.3095	1.1443
No log	21.0	63	0.9174	0.3794	0.9172	0.9577
No log	22.0	66	1.8867	0.1680	1.8866	1.3735
No log	23.0	69	0.8949	0.3724	0.8946	0.9458
No log	24.0	72	1.9165	0.1433	1.9164	1.3843
No log	25.0	75	0.9654	0.3476	0.9650	0.9823
No log	26.0	78	1.8161	0.1654	1.8162	1.3477
No log	27.0	81	0.9070	0.3606	0.9068	0.9522
No log	28.0	84	1.5505	0.2355	1.5507	1.2453
No log	29.0	87	0.8917	0.3901	0.8916	0.9442
No log	30.0	90	1.5399	0.2169	1.5401	1.2410
No log	31.0	93	0.9201	0.3443	0.9199	0.9591
No log	32.0	96	1.3771	0.2261	1.3771	1.1735
No log	33.0	99	1.0778	0.2771	1.0777	1.0381
No log	34.0	102	1.1479	0.2735	1.1479	1.0714
No log	35.0	105	1.4110	0.2689	1.4110	1.1879
No log	36.0	108	1.1979	0.2815	1.1979	1.0945
No log	37.0	111	1.2395	0.2576	1.2395	1.1133
No log	38.0	114	1.4691	0.1996	1.4694	1.2122
No log	39.0	117	1.1819	0.2236	1.1821	1.0872
No log	40.0	120	1.2787	0.2529	1.2790	1.1309
No log	41.0	123	1.0050	0.3557	1.0050	1.0025
No log	42.0	126	1.3945	0.2798	1.3947	1.1810
No log	43.0	129	1.0331	0.3307	1.0331	1.0164
No log	44.0	132	1.4993	0.2354	1.4995	1.2246
No log	45.0	135	1.0357	0.3024	1.0357	1.0177
No log	46.0	138	1.5430	0.2115	1.5433	1.2423
No log	47.0	141	1.0343	0.3006	1.0345	1.0171
No log	48.0	144	1.2975	0.2670	1.2978	1.1392
No log	49.0	147	1.0447	0.3033	1.0449	1.0222

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold2

ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold2