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	6.1732	0.0302	6.1737	2.4847
No log	2.0	12	2.6216	0.0658	2.6219	1.6192
No log	3.0	18	1.5140	0.0678	1.5143	1.2306
No log	4.0	24	1.2614	0.0384	1.2617	1.1233
No log	5.0	30	1.7649	0.0943	1.7646	1.3284
No log	6.0	36	1.6643	0.1172	1.6617	1.2891
No log	7.0	42	0.7650	0.2816	0.7648	0.8745
No log	8.0	48	1.1661	0.2756	1.1647	1.0792
No log	9.0	54	1.3957	0.2275	1.3935	1.1804
No log	10.0	60	1.2058	0.3504	1.2044	1.0975
No log	11.0	66	2.2708	0.1966	2.2687	1.5062
No log	12.0	72	1.2264	0.3071	1.2246	1.1066
No log	13.0	78	1.6487	0.2855	1.6470	1.2834
No log	14.0	84	1.1312	0.3770	1.1298	1.0629
No log	15.0	90	1.1826	0.3561	1.1811	1.0868
No log	16.0	96	1.1001	0.3735	1.0985	1.0481
No log	17.0	102	0.9614	0.4006	0.9601	0.9798
No log	18.0	108	1.6279	0.2255	1.6258	1.2751
No log	19.0	114	1.0607	0.4043	1.0591	1.0291
No log	20.0	120	0.8905	0.4327	0.8894	0.9431
No log	21.0	126	1.1477	0.3578	1.1459	1.0705
No log	22.0	132	1.3087	0.3386	1.3069	1.1432
No log	23.0	138	1.0803	0.4050	1.0787	1.0386
No log	24.0	144	1.2197	0.3576	1.2181	1.1037
No log	25.0	150	1.5230	0.2630	1.5210	1.2333
No log	26.0	156	0.9342	0.4073	0.9331	0.9660
No log	27.0	162	1.1272	0.3845	1.1258	1.0610
No log	28.0	168	1.0580	0.4084	1.0567	1.0280
No log	29.0	174	1.0131	0.4079	1.0122	1.0061
No log	30.0	180	1.3678	0.3379	1.3665	1.1690
No log	31.0	186	1.2062	0.4023	1.2048	1.0976
No log	32.0	192	1.0977	0.4196	1.0962	1.0470
No log	33.0	198	0.9936	0.4217	0.9923	0.9962
No log	34.0	204	1.1854	0.3711	1.1837	1.0880
No log	35.0	210	1.5252	0.3304	1.5232	1.2342
No log	36.0	216	1.0855	0.4261	1.0841	1.0412
No log	37.0	222	1.1536	0.3802	1.1520	1.0733
No log	38.0	228	1.0291	0.4445	1.0279	1.0138
No log	39.0	234	1.0380	0.4378	1.0368	1.0182
No log	40.0	240	1.1877	0.3511	1.1865	1.0893
No log	41.0	246	1.1099	0.3862	1.1086	1.0529
No log	42.0	252	0.9371	0.4250	0.9361	0.9675
No log	43.0	258	0.9579	0.4401	0.9567	0.9781
No log	44.0	264	1.1523	0.3884	1.1508	1.0728
No log	45.0	270	1.1110	0.3807	1.1096	1.0534
No log	46.0	276	0.9697	0.4243	0.9685	0.9841
No log	47.0	282	0.9150	0.4457	0.9140	0.9560
No log	48.0	288	0.9105	0.4591	0.9095	0.9537
No log	49.0	294	0.9281	0.4467	0.9270	0.9628
No log	50.0	300	0.9671	0.4250	0.9660	0.9828
No log	51.0	306	1.0665	0.4260	1.0651	1.0320
No log	52.0	312	1.0010	0.4647	0.9998	0.9999
No log	53.0	318	1.1143	0.4286	1.1128	1.0549
No log	54.0	324	1.4819	0.3131	1.4800	1.2166
No log	55.0	330	0.9992	0.4248	0.9977	0.9989
No log	56.0	336	1.4579	0.3256	1.4560	1.2066
No log	57.0	342	0.9169	0.4560	0.9157	0.9569
No log	58.0	348	1.2841	0.3730	1.2827	1.1326
No log	59.0	354	1.1831	0.4079	1.1818	1.0871
No log	60.0	360	0.9756	0.4371	0.9744	0.9871
No log	61.0	366	1.1431	0.4214	1.1416	1.0685
No log	62.0	372	1.2419	0.3783	1.2404	1.1137
No log	63.0	378	1.0860	0.4204	1.0844	1.0413
No log	64.0	384	1.0755	0.4194	1.0740	1.0363
No log	65.0	390	1.0232	0.4289	1.0218	1.0108
No log	66.0	396	0.9997	0.4331	0.9983	0.9991
No log	67.0	402	1.0627	0.4215	1.0613	1.0302
No log	68.0	408	1.1020	0.4030	1.1007	1.0491
No log	69.0	414	1.0479	0.3774	1.0466	1.0231
No log	70.0	420	1.0548	0.3903	1.0535	1.0264
No log	71.0	426	1.0361	0.4147	1.0347	1.0172
No log	72.0	432	1.4101	0.3406	1.4084	1.1868
No log	73.0	438	1.0780	0.4322	1.0764	1.0375
No log	74.0	444	1.2946	0.3690	1.2927	1.1370
No log	75.0	450	1.0017	0.4344	1.0000	1.0000
No log	76.0	456	1.1978	0.3617	1.1959	1.0936
No log	77.0	462	1.2757	0.3598	1.2737	1.1286
No log	78.0	468	1.0082	0.4273	1.0066	1.0033
No log	79.0	474	1.0020	0.4200	1.0005	1.0003
No log	80.0	480	1.0597	0.4276	1.0580	1.0286
No log	81.0	486	1.1305	0.3979	1.1287	1.0624
No log	82.0	492	0.9795	0.4278	0.9781	0.9890

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_fold2

Version24NewTestASAP_FineTuningBERT_AugV24_k10_task1_organization_k10_k10_fold2

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_fold2