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	4	5.8326	0.0544	5.8312	2.4148
No log	2.0	8	3.7777	0.0	3.7766	1.9433
No log	3.0	12	2.5893	-0.0206	2.5885	1.6089
No log	4.0	16	1.7257	0.0202	1.7249	1.3134
No log	5.0	20	1.4023	0.0266	1.4016	1.1839
No log	6.0	24	1.1052	0.0427	1.1046	1.0510
No log	7.0	28	1.6257	0.1928	1.6250	1.2748
No log	8.0	32	1.1062	0.1567	1.1059	1.0516
No log	9.0	36	1.0997	0.1887	1.0997	1.0486
No log	10.0	40	0.9966	0.2999	0.9967	0.9983
No log	11.0	44	0.7123	0.4626	0.7125	0.8441
No log	12.0	48	1.5498	0.2421	1.5498	1.2449
No log	13.0	52	0.7264	0.4238	0.7266	0.8524
No log	14.0	56	1.2653	0.2977	1.2658	1.1251
No log	15.0	60	0.7535	0.4251	0.7541	0.8684
No log	16.0	64	1.6099	0.2357	1.6105	1.2691
No log	17.0	68	1.2342	0.3381	1.2348	1.1112
No log	18.0	72	0.9063	0.4456	0.9068	0.9523
No log	19.0	76	1.0804	0.3312	1.0808	1.0396
No log	20.0	80	0.9214	0.4140	0.9220	0.9602
No log	21.0	84	1.1702	0.3241	1.1708	1.0820
No log	22.0	88	1.2224	0.3383	1.2228	1.1058
No log	23.0	92	1.0446	0.4186	1.0448	1.0222
No log	24.0	96	1.5922	0.2895	1.5925	1.2619
No log	25.0	100	1.0999	0.3945	1.0997	1.0486
No log	26.0	104	1.1617	0.3359	1.1618	1.0779
No log	27.0	108	1.0284	0.4094	1.0292	1.0145
No log	28.0	112	0.9066	0.4757	0.9075	0.9526
No log	29.0	116	1.1233	0.4109	1.1244	1.0604
No log	30.0	120	1.2542	0.3512	1.2545	1.1200
No log	31.0	124	0.9608	0.4248	0.9615	0.9805
No log	32.0	128	1.0291	0.4066	1.0299	1.0148
No log	33.0	132	1.0585	0.4036	1.0595	1.0293
No log	34.0	136	1.0541	0.3972	1.0550	1.0271
No log	35.0	140	1.0312	0.4189	1.0320	1.0159
No log	36.0	144	0.9826	0.4283	0.9831	0.9915
No log	37.0	148	1.0161	0.4304	1.0163	1.0081
No log	38.0	152	1.2375	0.3315	1.2380	1.1127
No log	39.0	156	0.9432	0.4245	0.9436	0.9714
No log	40.0	160	0.9376	0.3812	0.9384	0.9687
No log	41.0	164	0.9509	0.4388	0.9517	0.9756
No log	42.0	168	1.0913	0.4074	1.0923	1.0451
No log	43.0	172	1.0319	0.4588	1.0327	1.0162
No log	44.0	176	1.1438	0.4067	1.1450	1.0701
No log	45.0	180	1.1030	0.4019	1.1038	1.0506
No log	46.0	184	0.9294	0.4343	0.9300	0.9644
No log	47.0	188	0.9620	0.3906	0.9626	0.9811
No log	48.0	192	1.0013	0.4369	1.0017	1.0009

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3