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	2	11.8129	0.0089	11.8110	3.4367
No log	2.0	4	9.5040	0.0036	9.5024	3.0826
No log	3.0	6	6.9971	0.0	6.9958	2.6450
No log	4.0	8	5.4072	0.0259	5.4060	2.3251
No log	5.0	10	4.2886	0.0076	4.2876	2.0707
No log	6.0	12	3.0337	0.0	3.0328	1.7415
No log	7.0	14	2.5282	0.0424	2.5273	1.5897
No log	8.0	16	1.8780	0.0539	1.8773	1.3701
No log	9.0	18	1.5740	0.0365	1.5734	1.2543
No log	10.0	20	1.2760	0.0202	1.2754	1.1293
No log	11.0	22	1.2368	0.0266	1.2363	1.1119
No log	12.0	24	1.5645	0.0599	1.5640	1.2506
No log	13.0	26	1.9070	0.1649	1.9066	1.3808
No log	14.0	28	1.3112	0.0976	1.3110	1.1450
No log	15.0	30	1.0201	0.0809	1.0196	1.0098
No log	16.0	32	1.0418	0.0953	1.0415	1.0205
No log	17.0	34	1.2590	0.1719	1.2592	1.1222
No log	18.0	36	0.9619	0.3477	0.9623	0.9810
No log	19.0	38	0.8347	0.3251	0.8347	0.9136
No log	20.0	40	0.8591	0.3277	0.8595	0.9271
No log	21.0	42	1.0814	0.2778	1.0820	1.0402
No log	22.0	44	0.9222	0.3101	0.9228	0.9606
No log	23.0	46	0.9539	0.3216	0.9548	0.9771
No log	24.0	48	1.3909	0.2605	1.3918	1.1798
No log	25.0	50	1.0724	0.3406	1.0735	1.0361
No log	26.0	52	1.0923	0.3397	1.0934	1.0457
No log	27.0	54	1.3708	0.2715	1.3718	1.1713
No log	28.0	56	1.1858	0.3080	1.1869	1.0894
No log	29.0	58	1.3028	0.2819	1.3039	1.1419
No log	30.0	60	1.3531	0.2686	1.3541	1.1637
No log	31.0	62	1.1704	0.2929	1.1714	1.0823
No log	32.0	64	1.1873	0.3213	1.1883	1.0901
No log	33.0	66	1.1808	0.3201	1.1820	1.0872
No log	34.0	68	1.0454	0.3389	1.0467	1.0231
No log	35.0	70	1.2394	0.2804	1.2408	1.1139
No log	36.0	72	1.1353	0.3155	1.1367	1.0662
No log	37.0	74	1.1094	0.3314	1.1107	1.0539
No log	38.0	76	1.1378	0.3049	1.1392	1.0673
No log	39.0	78	1.2223	0.2717	1.2236	1.1062
No log	40.0	80	1.1041	0.3493	1.1053	1.0513
No log	41.0	82	1.3059	0.2974	1.3070	1.1432
No log	42.0	84	1.2883	0.2983	1.2894	1.1355
No log	43.0	86	1.1200	0.3549	1.1211	1.0588
No log	44.0	88	1.2260	0.3040	1.2272	1.1078
No log	45.0	90	1.1507	0.3281	1.1519	1.0733
No log	46.0	92	1.1265	0.3758	1.1276	1.0619
No log	47.0	94	1.1552	0.3756	1.1564	1.0754
No log	48.0	96	1.2980	0.2926	1.2993	1.1399
No log	49.0	98	1.1874	0.3519	1.1886	1.0902
No log	50.0	100	1.0971	0.3816	1.0980	1.0479
No log	51.0	102	1.0797	0.3795	1.0806	1.0395
No log	52.0	104	1.1970	0.2880	1.1980	1.0945
No log	53.0	106	1.0542	0.3845	1.0551	1.0272
No log	54.0	108	1.0633	0.4218	1.0642	1.0316
No log	55.0	110	1.1026	0.4219	1.1036	1.0505
No log	56.0	112	1.1619	0.3802	1.1630	1.0784
No log	57.0	114	1.1425	0.4003	1.1435	1.0694
No log	58.0	116	1.0939	0.4344	1.0948	1.0463
No log	59.0	118	1.0387	0.4370	1.0395	1.0196
No log	60.0	120	1.1274	0.3514	1.1284	1.0622
No log	61.0	122	1.1427	0.3499	1.1436	1.0694
No log	62.0	124	0.9939	0.4304	0.9947	0.9974
No log	63.0	126	0.9849	0.4380	0.9857	0.9928
No log	64.0	128	1.0217	0.3931	1.0226	1.0112
No log	65.0	130	1.0417	0.3912	1.0425	1.0210
No log	66.0	132	1.0261	0.4127	1.0269	1.0133
No log	67.0	134	1.0458	0.3951	1.0467	1.0231
No log	68.0	136	1.1512	0.3248	1.1522	1.0734
No log	69.0	138	1.1300	0.3594	1.1310	1.0635
No log	70.0	140	1.0697	0.4078	1.0706	1.0347
No log	71.0	142	1.0453	0.4368	1.0462	1.0228
No log	72.0	144	1.0452	0.4113	1.0461	1.0228
No log	73.0	146	1.0291	0.4194	1.0300	1.0149
No log	74.0	148	1.0138	0.4461	1.0145	1.0072
No log	75.0	150	1.0266	0.4071	1.0274	1.0136
No log	76.0	152	1.0679	0.3871	1.0687	1.0338
No log	77.0	154	1.0569	0.3881	1.0576	1.0284
No log	78.0	156	0.9948	0.4189	0.9955	0.9977
No log	79.0	158	0.9945	0.4231	0.9952	0.9976
No log	80.0	160	1.0311	0.3880	1.0319	1.0158
No log	81.0	162	1.0663	0.3724	1.0671	1.0330
No log	82.0	164	1.0693	0.3895	1.0701	1.0344
No log	83.0	166	1.0607	0.4144	1.0615	1.0303
No log	84.0	168	1.0658	0.4184	1.0665	1.0327
No log	85.0	170	1.0794	0.4004	1.0802	1.0393
No log	86.0	172	1.1116	0.3768	1.1125	1.0547
No log	87.0	174	1.1099	0.3611	1.1108	1.0540
No log	88.0	176	1.0654	0.4018	1.0662	1.0326
No log	89.0	178	1.0215	0.4120	1.0223	1.0111
No log	90.0	180	1.0047	0.4340	1.0054	1.0027
No log	91.0	182	0.9995	0.4194	1.0002	1.0001
No log	92.0	184	1.0124	0.4127	1.0132	1.0066
No log	93.0	186	1.0308	0.4005	1.0316	1.0157
No log	94.0	188	1.0332	0.3997	1.0341	1.0169
No log	95.0	190	1.0208	0.4083	1.0216	1.0107
No log	96.0	192	1.0138	0.4181	1.0146	1.0073
No log	97.0	194	1.0098	0.4173	1.0105	1.0053
No log	98.0	196	1.0099	0.4149	1.0107	1.0053
No log	99.0	198	1.0114	0.4172	1.0121	1.0061
No log	100.0	200	1.0122	0.4172	1.0129	1.0065

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version22NewTestASAP_FineTuningBERT_AugV22_k3_task1_organization_k3_k3_fold3

Version22NewTestASAP_FineTuningBERT_AugV22_k3_task1_organization_k3_k3_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version22NewTestASAP_FineTuningBERT_AugV22_k3_task1_organization_k3_k3_fold3