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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	3	8.1148	0.0	8.1148	2.8487
No log	2.0	6	6.8463	0.0	6.8463	2.6165
No log	3.0	9	5.5379	0.0109	5.5379	2.3533
No log	4.0	12	4.3614	0.0077	4.3614	2.0884
No log	5.0	15	3.1667	0.0	3.1667	1.7795
No log	6.0	18	2.1598	0.0689	2.1598	1.4696
No log	7.0	21	1.5239	0.0316	1.5239	1.2345
No log	8.0	24	1.1988	0.0316	1.1988	1.0949
No log	9.0	27	1.4014	0.1026	1.4014	1.1838
No log	10.0	30	1.0868	0.0873	1.0868	1.0425
No log	11.0	33	1.3233	0.1776	1.3233	1.1503
No log	12.0	36	0.9855	0.3111	0.9855	0.9927
No log	13.0	39	0.9753	0.3353	0.9753	0.9876
No log	14.0	42	0.7413	0.4028	0.7413	0.8610
No log	15.0	45	0.7715	0.4180	0.7715	0.8783
No log	16.0	48	0.6273	0.4278	0.6273	0.7920
No log	17.0	51	0.7917	0.4143	0.7917	0.8898
No log	18.0	54	0.6792	0.4114	0.6792	0.8242
No log	19.0	57	0.7400	0.4167	0.7400	0.8602
No log	20.0	60	0.7616	0.4333	0.7616	0.8727
No log	21.0	63	0.6550	0.4743	0.6550	0.8093
No log	22.0	66	0.5888	0.4953	0.5888	0.7674
No log	23.0	69	0.6041	0.5105	0.6041	0.7772
No log	24.0	72	0.5932	0.5209	0.5932	0.7702
No log	25.0	75	0.6666	0.4916	0.6666	0.8165
No log	26.0	78	0.6326	0.5005	0.6326	0.7954
No log	27.0	81	0.7404	0.4665	0.7404	0.8605
No log	28.0	84	0.6357	0.5073	0.6357	0.7973
No log	29.0	87	0.5410	0.5471	0.5410	0.7355
No log	30.0	90	0.6886	0.5190	0.6886	0.8298
No log	31.0	93	0.5554	0.5708	0.5554	0.7452
No log	32.0	96	0.5631	0.5429	0.5631	0.7504
No log	33.0	99	0.6768	0.5330	0.6768	0.8227
No log	34.0	102	0.6213	0.5312	0.6213	0.7882
No log	35.0	105	0.5816	0.5385	0.5816	0.7626
No log	36.0	108	0.6681	0.5489	0.6681	0.8173
No log	37.0	111	0.6559	0.5575	0.6559	0.8099
No log	38.0	114	0.6228	0.5433	0.6228	0.7892
No log	39.0	117	0.6738	0.5512	0.6738	0.8208
No log	40.0	120	0.5851	0.5861	0.5851	0.7649
No log	41.0	123	0.6149	0.5626	0.6149	0.7842
No log	42.0	126	0.7908	0.5343	0.7908	0.8893
No log	43.0	129	0.6199	0.5761	0.6199	0.7874
No log	44.0	132	0.6159	0.5578	0.6159	0.7848
No log	45.0	135	0.5630	0.6153	0.5630	0.7503
No log	46.0	138	0.7283	0.4835	0.7283	0.8534
No log	47.0	141	0.6453	0.5910	0.6453	0.8033
No log	48.0	144	0.7176	0.5634	0.7176	0.8471
No log	49.0	147	0.6241	0.5770	0.6241	0.7900
No log	50.0	150	0.6116	0.5500	0.6116	0.7821
No log	51.0	153	0.6043	0.5962	0.6043	0.7774
No log	52.0	156	0.5826	0.5888	0.5826	0.7633
No log	53.0	159	0.5826	0.6111	0.5826	0.7633
No log	54.0	162	0.7139	0.5095	0.7139	0.8449
No log	55.0	165	0.6991	0.5654	0.6991	0.8362
No log	56.0	168	0.6732	0.5502	0.6732	0.8205
No log	57.0	171	0.6763	0.5402	0.6763	0.8224
No log	58.0	174	0.5778	0.5792	0.5778	0.7601
No log	59.0	177	0.5623	0.5911	0.5623	0.7498
No log	60.0	180	0.6489	0.4982	0.6489	0.8055
No log	61.0	183	0.5749	0.6112	0.5749	0.7582
No log	62.0	186	0.6388	0.5883	0.6388	0.7992
No log	63.0	189	0.6617	0.5811	0.6617	0.8135
No log	64.0	192	0.6355	0.5055	0.6355	0.7972
No log	65.0	195	0.6092	0.5169	0.6092	0.7805
No log	66.0	198	0.5553	0.5925	0.5553	0.7452
No log	67.0	201	0.6414	0.5918	0.6414	0.8009
No log	68.0	204	0.7029	0.5522	0.7029	0.8384
No log	69.0	207	0.5908	0.5533	0.5908	0.7686
No log	70.0	210	0.5841	0.5775	0.5841	0.7643
No log	71.0	213	0.6206	0.5755	0.6206	0.7878
No log	72.0	216	0.6494	0.5831	0.6494	0.8058
No log	73.0	219	0.5953	0.6078	0.5953	0.7716
No log	74.0	222	0.5385	0.5951	0.5385	0.7338
No log	75.0	225	0.5521	0.5927	0.5521	0.7430

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version24NewTestASAP_FineTuningBERT_AugV24_k5_task1_organization_k5_k5_fold0

Version24NewTestASAP_FineTuningBERT_AugV24_k5_task1_organization_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version24NewTestASAP_FineTuningBERT_AugV24_k5_task1_organization_k5_k5_fold0