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	9.7385	0.0018	9.7386	3.1207
No log	2.0	4	7.6807	0.0	7.6808	2.7714
No log	3.0	6	6.8232	0.0	6.8234	2.6122
No log	4.0	8	5.3821	0.0167	5.3824	2.3200
No log	5.0	10	4.4631	0.0025	4.4634	2.1127
No log	6.0	12	3.3333	0.0	3.3337	1.8259
No log	7.0	14	2.5197	0.0161	2.5201	1.5875
No log	8.0	16	1.9588	0.1362	1.9593	1.3998
No log	9.0	18	1.6210	0.0241	1.6214	1.2734
No log	10.0	20	1.2718	0.0241	1.2723	1.1279
No log	11.0	22	0.9821	0.0107	0.9825	0.9912
No log	12.0	24	0.8332	0.2587	0.8336	0.9130
No log	13.0	26	0.7609	0.3129	0.7612	0.8725
No log	14.0	28	0.8105	0.1086	0.8108	0.9005
No log	15.0	30	0.6841	0.2329	0.6842	0.8271
No log	16.0	32	0.8690	0.1079	0.8692	0.9323
No log	17.0	34	0.7003	0.2281	0.6999	0.8366
No log	18.0	36	0.6059	0.3647	0.6058	0.7783
No log	19.0	38	0.6928	0.3389	0.6923	0.8321
No log	20.0	40	0.7073	0.5128	0.7065	0.8406
No log	21.0	42	0.6554	0.5454	0.6547	0.8091
No log	22.0	44	0.8270	0.5237	0.8258	0.9087
No log	23.0	46	0.8851	0.5228	0.8842	0.9403
No log	24.0	48	0.9898	0.5073	0.9886	0.9943
No log	25.0	50	1.1040	0.5035	1.1028	1.0501
No log	26.0	52	1.4832	0.3617	1.4825	1.2176
No log	27.0	54	1.2145	0.3955	1.2138	1.1017
No log	28.0	56	0.7176	0.5656	0.7167	0.8466
No log	29.0	58	0.7389	0.5439	0.7379	0.8590
No log	30.0	60	0.6807	0.5556	0.6800	0.8246
No log	31.0	62	0.6875	0.6021	0.6869	0.8288
No log	32.0	64	0.6946	0.6105	0.6942	0.8332
No log	33.0	66	0.9573	0.5435	0.9563	0.9779
No log	34.0	68	1.0433	0.5260	1.0422	1.0209
No log	35.0	70	0.8191	0.5998	0.8184	0.9047
No log	36.0	72	0.8988	0.5792	0.8981	0.9477
No log	37.0	74	0.8953	0.5927	0.8948	0.9459
No log	38.0	76	1.1216	0.5346	1.1205	1.0586
No log	39.0	78	1.0211	0.5536	1.0202	1.0101
No log	40.0	80	0.7562	0.5954	0.7559	0.8694
No log	41.0	82	0.9355	0.5499	0.9347	0.9668
No log	42.0	84	1.1286	0.5025	1.1276	1.0619
No log	43.0	86	0.6846	0.5807	0.6843	0.8272
No log	44.0	88	0.6637	0.5895	0.6634	0.8145
No log	45.0	90	1.2286	0.4627	1.2275	1.1079
No log	46.0	92	1.5381	0.4125	1.5368	1.2397
No log	47.0	94	0.8898	0.5350	0.8891	0.9429
No log	48.0	96	0.6399	0.5833	0.6397	0.7998
No log	49.0	98	0.6404	0.5891	0.6400	0.8000
No log	50.0	100	1.1204	0.4795	1.1194	1.0580
No log	51.0	102	1.4537	0.4353	1.4525	1.2052
No log	52.0	104	0.9626	0.5283	0.9617	0.9807

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version5ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2

Version5ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version5ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2