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	6	7.3404	0.0054	7.3404	2.7093
No log	2.0	12	3.9655	0.0115	3.9655	1.9914
No log	3.0	18	2.0484	0.0572	2.0484	1.4312
No log	4.0	24	1.2793	0.0715	1.2793	1.1311
No log	5.0	30	1.3766	0.1006	1.3766	1.1733
No log	6.0	36	2.2167	0.1624	2.2167	1.4889
No log	7.0	42	0.9884	0.0715	0.9884	0.9942
No log	8.0	48	1.7817	0.1428	1.7817	1.3348
No log	9.0	54	1.3390	0.0715	1.3390	1.1572
No log	10.0	60	1.1567	0.0715	1.1567	1.0755
No log	11.0	66	1.4849	0.1314	1.4849	1.2185
No log	12.0	72	1.0167	0.0923	1.0167	1.0083
No log	13.0	78	1.2459	0.1520	1.2459	1.1162
No log	14.0	84	0.8965	0.1006	0.8965	0.9468
No log	15.0	90	1.1180	0.1394	1.1180	1.0574
No log	16.0	96	0.8121	0.3252	0.8121	0.9011
No log	17.0	102	0.8309	0.3636	0.8309	0.9116
No log	18.0	108	0.7249	0.4075	0.7249	0.8514
No log	19.0	114	0.6726	0.4270	0.6726	0.8201
No log	20.0	120	0.6995	0.4514	0.6995	0.8364
No log	21.0	126	0.6474	0.4421	0.6474	0.8046
No log	22.0	132	0.6777	0.4767	0.6777	0.8232
No log	23.0	138	0.7425	0.3650	0.7425	0.8617
No log	24.0	144	0.8002	0.3540	0.8002	0.8946
No log	25.0	150	0.7971	0.4138	0.7971	0.8928
No log	26.0	156	0.8376	0.4291	0.8376	0.9152
No log	27.0	162	0.7546	0.4946	0.7546	0.8687
No log	28.0	168	0.9389	0.4196	0.9389	0.9690
No log	29.0	174	0.6853	0.5199	0.6853	0.8278
No log	30.0	180	0.9591	0.4497	0.9591	0.9793
No log	31.0	186	0.7349	0.4909	0.7349	0.8572
No log	32.0	192	0.9860	0.4194	0.9860	0.9930
No log	33.0	198	1.7762	0.2817	1.7762	1.3328
No log	34.0	204	0.7699	0.4860	0.7699	0.8775
No log	35.0	210	1.1488	0.4262	1.1488	1.0718
No log	36.0	216	1.1006	0.4153	1.1006	1.0491
No log	37.0	222	1.7816	0.3045	1.7816	1.3348
No log	38.0	228	1.0930	0.4197	1.0930	1.0454
No log	39.0	234	1.0783	0.4441	1.0783	1.0384
No log	40.0	240	1.5631	0.3363	1.5631	1.2502
No log	41.0	246	0.9181	0.4552	0.9181	0.9582
No log	42.0	252	1.5727	0.3599	1.5727	1.2541
No log	43.0	258	1.8694	0.3149	1.8694	1.3672
No log	44.0	264	1.0176	0.4689	1.0176	1.0088
No log	45.0	270	1.0865	0.4374	1.0865	1.0424
No log	46.0	276	1.6822	0.3361	1.6822	1.2970
No log	47.0	282	0.9710	0.4463	0.9710	0.9854
No log	48.0	288	1.1321	0.4251	1.1321	1.0640
No log	49.0	294	1.7759	0.3204	1.7759	1.3326

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_fold0

ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_fold0