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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	6	8.9483	0.0	8.9455	2.9909
No log	2.0	12	4.8553	0.0185	4.8531	2.2030
No log	3.0	18	2.4207	0.0165	2.4188	1.5553
No log	4.0	24	1.7817	0.0495	1.7803	1.3343
No log	5.0	30	1.6623	0.1011	1.6608	1.2887
No log	6.0	36	1.8773	0.1747	1.8758	1.3696
No log	7.0	42	2.0322	0.1897	2.0306	1.4250
No log	8.0	48	1.1985	0.1472	1.1974	1.0943
No log	9.0	54	1.0804	0.1742	1.0794	1.0389
No log	10.0	60	2.0534	0.1531	2.0520	1.4325
No log	11.0	66	2.7865	0.0342	2.7852	1.6689
No log	12.0	72	2.7544	0.0419	2.7535	1.6594
No log	13.0	78	2.3346	0.0593	2.3341	1.5278
No log	14.0	84	1.8918	0.0133	1.8913	1.3752
No log	15.0	90	2.1150	0.0198	2.1144	1.4541
No log	16.0	96	2.1376	0.0039	2.1367	1.4617
No log	17.0	102	1.5578	0.0905	1.5570	1.2478
No log	18.0	108	1.5395	0.1411	1.5387	1.2404
No log	19.0	114	1.4661	0.1512	1.4652	1.2104
No log	20.0	120	1.9018	0.0642	1.9005	1.3786
No log	21.0	126	2.0744	0.0733	2.0732	1.4398
No log	22.0	132	2.3189	0.0388	2.3174	1.5223
No log	23.0	138	2.0526	0.0590	2.0513	1.4322
No log	24.0	144	2.4185	0.0179	2.4171	1.5547
No log	25.0	150	1.1952	0.2128	1.1946	1.0930
No log	26.0	156	1.7811	0.1231	1.7802	1.3343
No log	27.0	162	2.5676	0.0332	2.5662	1.6019
No log	28.0	168	1.3193	0.1740	1.3185	1.1483
No log	29.0	174	1.1646	0.2043	1.1639	1.0788
No log	30.0	180	1.1532	0.2244	1.1524	1.0735
No log	31.0	186	1.1218	0.2578	1.1212	1.0588
No log	32.0	192	1.7647	0.1831	1.7636	1.3280
No log	33.0	198	1.1049	0.2991	1.1040	1.0507
No log	34.0	204	0.9916	0.2819	0.9910	0.9955
No log	35.0	210	1.1519	0.2641	1.1514	1.0730
No log	36.0	216	1.0862	0.2487	1.0855	1.0419
No log	37.0	222	1.4576	0.2327	1.4565	1.2069
No log	38.0	228	1.2706	0.3189	1.2697	1.1268
No log	39.0	234	1.8217	0.1850	1.8205	1.3493
No log	40.0	240	1.2549	0.2653	1.2540	1.1198
No log	41.0	246	0.9905	0.3433	0.9899	0.9949
No log	42.0	252	1.2922	0.2503	1.2915	1.1364
No log	43.0	258	1.1048	0.3069	1.1041	1.0508
No log	44.0	264	0.9553	0.3550	0.9546	0.9771
No log	45.0	270	1.0418	0.3222	1.0409	1.0203
No log	46.0	276	0.9888	0.3173	0.9880	0.9940
No log	47.0	282	0.9947	0.3605	0.9941	0.9970
No log	48.0	288	1.0782	0.3608	1.0775	1.0380
No log	49.0	294	1.3578	0.2818	1.3568	1.1648
No log	50.0	300	0.9403	0.3642	0.9397	0.9694
No log	51.0	306	1.0497	0.3361	1.0489	1.0242
No log	52.0	312	1.1081	0.3039	1.1072	1.0522
No log	53.0	318	1.5600	0.1749	1.5588	1.2485
No log	54.0	324	0.9934	0.3245	0.9927	0.9964
No log	55.0	330	1.0266	0.2989	1.0258	1.0128
No log	56.0	336	1.1845	0.2632	1.1837	1.0880
No log	57.0	342	1.0164	0.3139	1.0157	1.0078
No log	58.0	348	0.8796	0.3394	0.8790	0.9375
No log	59.0	354	0.9980	0.3270	0.9973	0.9986
No log	60.0	360	1.3128	0.2467	1.3121	1.1455
No log	61.0	366	1.2433	0.2346	1.2425	1.1147
No log	62.0	372	0.8811	0.3482	0.8806	0.9384
No log	63.0	378	1.2153	0.2348	1.2144	1.1020
No log	64.0	384	1.3285	0.2347	1.3276	1.1522
No log	65.0	390	0.9525	0.3126	0.9518	0.9756
No log	66.0	396	0.9654	0.3028	0.9646	0.9821
No log	67.0	402	1.3212	0.2079	1.3201	1.1489
No log	68.0	408	1.2871	0.2008	1.2860	1.1340
No log	69.0	414	0.9744	0.3210	0.9737	0.9867
No log	70.0	420	1.0035	0.3034	1.0027	1.0013
No log	71.0	426	1.1169	0.2638	1.1159	1.0564
No log	72.0	432	0.9275	0.3059	0.9267	0.9627
No log	73.0	438	0.9620	0.3096	0.9612	0.9804
No log	74.0	444	1.0172	0.2896	1.0163	1.0081
No log	75.0	450	0.9594	0.2975	0.9584	0.9790
No log	76.0	456	0.9584	0.3005	0.9574	0.9785
No log	77.0	462	1.1112	0.2643	1.1102	1.0536
No log	78.0	468	1.2506	0.2419	1.2496	1.1178
No log	79.0	474	0.9736	0.3123	0.9728	0.9863
No log	80.0	480	1.0007	0.3261	0.9998	0.9999

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version24NewTestASAP_FineTuningBERT_AugV24_k10_task1_organization_k10_k10_fold1

Version24NewTestASAP_FineTuningBERT_AugV24_k10_task1_organization_k10_k10_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version24NewTestASAP_FineTuningBERT_AugV24_k10_task1_organization_k10_k10_fold1