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	11.0669	0.0	11.0669	3.3267
No log	2.0	4	9.1533	0.0	9.1533	3.0254
No log	3.0	6	7.4022	0.0	7.4022	2.7207
No log	4.0	8	5.9410	0.0031	5.9410	2.4374
No log	5.0	10	5.2421	0.0	5.2421	2.2896
No log	6.0	12	4.0284	0.0	4.0284	2.0071
No log	7.0	14	3.2575	0.0	3.2575	1.8049
No log	8.0	16	2.8362	0.0467	2.8362	1.6841
No log	9.0	18	2.2505	0.0	2.2505	1.5002
No log	10.0	20	1.9634	0.0	1.9634	1.4012
No log	11.0	22	1.7014	0.0	1.7014	1.3044
No log	12.0	24	1.6510	0.0	1.6510	1.2849
No log	13.0	26	1.2322	0.0	1.2322	1.1101
No log	14.0	28	1.1089	0.0	1.1089	1.0530
No log	15.0	30	0.9749	0.0369	0.9749	0.9874
No log	16.0	32	1.2424	0.0	1.2424	1.1146
No log	17.0	34	1.0784	0.0718	1.0784	1.0385
No log	18.0	36	0.8415	0.3159	0.8415	0.9173
No log	19.0	38	0.9689	0.1982	0.9689	0.9843
No log	20.0	40	0.8746	0.3469	0.8746	0.9352
No log	21.0	42	0.7865	0.2619	0.7865	0.8869
No log	22.0	44	0.7331	0.3040	0.7331	0.8562
No log	23.0	46	0.6743	0.2740	0.6743	0.8212
No log	24.0	48	0.6912	0.3290	0.6912	0.8314
No log	25.0	50	0.5790	0.2796	0.5790	0.7609
No log	26.0	52	0.5721	0.3233	0.5721	0.7564
No log	27.0	54	0.5570	0.3034	0.5570	0.7463
No log	28.0	56	0.8042	0.3846	0.8042	0.8968
No log	29.0	58	0.8784	0.3937	0.8784	0.9372
No log	30.0	60	0.5822	0.5050	0.5822	0.7630
No log	31.0	62	0.5774	0.5197	0.5774	0.7598
No log	32.0	64	0.7956	0.4815	0.7956	0.8920
No log	33.0	66	0.6278	0.5588	0.6278	0.7924
No log	34.0	68	0.5590	0.5481	0.5590	0.7477
No log	35.0	70	0.5991	0.5416	0.5991	0.7740
No log	36.0	72	0.8284	0.4800	0.8284	0.9102
No log	37.0	74	0.7120	0.5310	0.7120	0.8438
No log	38.0	76	0.6731	0.5426	0.6731	0.8205
No log	39.0	78	0.6834	0.5310	0.6834	0.8267
No log	40.0	80	0.9715	0.4040	0.9715	0.9857
No log	41.0	82	0.7605	0.5238	0.7605	0.8721
No log	42.0	84	0.6342	0.4889	0.6342	0.7963
No log	43.0	86	0.6225	0.5063	0.6225	0.7890
No log	44.0	88	0.7466	0.5561	0.7466	0.8641
No log	45.0	90	0.7751	0.5345	0.7751	0.8804
No log	46.0	92	0.6728	0.4956	0.6728	0.8202
No log	47.0	94	0.7035	0.4527	0.7035	0.8388
No log	48.0	96	0.6778	0.4728	0.6778	0.8233
No log	49.0	98	0.6762	0.4979	0.6762	0.8223
No log	50.0	100	0.6497	0.4932	0.6497	0.8060
No log	51.0	102	0.6747	0.5038	0.6747	0.8214
No log	52.0	104	0.6572	0.5199	0.6572	0.8107
No log	53.0	106	0.6868	0.4721	0.6868	0.8287

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3