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	5.1723	0.0198	5.1711	2.2740
No log	2.0	12	2.5949	0.0072	2.5941	1.6106
No log	3.0	18	1.1212	0.0	1.1207	1.0586
No log	4.0	24	1.0716	0.0	1.0711	1.0349
No log	5.0	30	1.3938	0.0365	1.3931	1.1803
No log	6.0	36	1.0449	0.0810	1.0444	1.0219
No log	7.0	42	0.7668	0.4401	0.7666	0.8756
No log	8.0	48	0.7108	0.4813	0.7107	0.8430
No log	9.0	54	0.6066	0.5136	0.6068	0.7790
No log	10.0	60	0.5790	0.5388	0.5792	0.7610
No log	11.0	66	0.5832	0.5292	0.5836	0.7639
No log	12.0	72	0.6515	0.5646	0.6519	0.8074
No log	13.0	78	0.7128	0.5887	0.7132	0.8445
No log	14.0	84	0.7234	0.6013	0.7235	0.8506
No log	15.0	90	0.7278	0.5961	0.7278	0.8531
No log	16.0	96	0.7546	0.5789	0.7547	0.8687
No log	17.0	102	0.7844	0.5561	0.7845	0.8857
No log	18.0	108	0.7720	0.5383	0.7724	0.8789
No log	19.0	114	0.8749	0.5172	0.8753	0.9356
No log	20.0	120	0.6382	0.6014	0.6385	0.7991
No log	21.0	126	0.8267	0.5406	0.8269	0.9094
No log	22.0	132	0.6766	0.5885	0.6769	0.8228
No log	23.0	138	0.6698	0.5799	0.6701	0.8186
No log	24.0	144	0.6954	0.5908	0.6956	0.8340
No log	25.0	150	0.6814	0.5922	0.6816	0.8256
No log	26.0	156	0.7229	0.5815	0.7232	0.8504
No log	27.0	162	0.6571	0.5906	0.6574	0.8108
No log	28.0	168	0.7996	0.5664	0.7998	0.8943
No log	29.0	174	0.6206	0.6018	0.6208	0.7879
No log	30.0	180	0.6596	0.5807	0.6599	0.8124
No log	31.0	186	0.6924	0.5879	0.6927	0.8323
No log	32.0	192	0.6748	0.5853	0.6751	0.8216
No log	33.0	198	0.6863	0.5803	0.6866	0.8286
No log	34.0	204	0.6991	0.5815	0.6994	0.8363
No log	35.0	210	0.7769	0.5536	0.7772	0.8816
No log	36.0	216	0.6561	0.5764	0.6563	0.8101
No log	37.0	222	0.6831	0.5820	0.6834	0.8267
No log	38.0	228	0.6403	0.5988	0.6406	0.8004
No log	39.0	234	0.6625	0.5806	0.6628	0.8142
No log	40.0	240	0.6493	0.5663	0.6496	0.8060
No log	41.0	246	0.6646	0.5819	0.6648	0.8154
No log	42.0	252	0.6460	0.5801	0.6462	0.8039
No log	43.0	258	0.6913	0.5834	0.6914	0.8315
No log	44.0	264	0.6536	0.5775	0.6539	0.8086
No log	45.0	270	0.6339	0.5816	0.6342	0.7964
No log	46.0	276	0.6760	0.5623	0.6763	0.8224
No log	47.0	282	0.6590	0.5631	0.6593	0.8120
No log	48.0	288	0.6643	0.5884	0.6645	0.8152
No log	49.0	294	0.6449	0.5830	0.6452	0.8032

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold3

ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold3