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	4	7.2376	0.0	7.2376	2.6903
No log	2.0	8	4.2359	0.0079	4.2359	2.0581
No log	3.0	12	2.7472	0.0040	2.7472	1.6575
No log	4.0	16	1.6405	0.0239	1.6405	1.2808
No log	5.0	20	1.1662	0.0213	1.1662	1.0799
No log	6.0	24	1.9150	0.1919	1.9150	1.3838
No log	7.0	28	1.2333	0.0844	1.2333	1.1105
No log	8.0	32	1.0954	0.0760	1.0954	1.0466
No log	9.0	36	1.2273	0.1898	1.2273	1.1078
No log	10.0	40	1.0855	0.2761	1.0855	1.0419
No log	11.0	44	0.7194	0.4126	0.7194	0.8482
No log	12.0	48	0.8837	0.4441	0.8837	0.9400
No log	13.0	52	0.5997	0.4735	0.5997	0.7744
No log	14.0	56	0.7489	0.4875	0.7489	0.8654
No log	15.0	60	0.7349	0.5018	0.7349	0.8573
No log	16.0	64	0.7272	0.5055	0.7272	0.8527
No log	17.0	68	0.7233	0.5565	0.7233	0.8505
No log	18.0	72	0.7206	0.5664	0.7206	0.8489
No log	19.0	76	0.7480	0.5191	0.7480	0.8649
No log	20.0	80	0.7625	0.5191	0.7625	0.8732
No log	21.0	84	0.7027	0.5558	0.7027	0.8383
No log	22.0	88	0.7984	0.4887	0.7984	0.8935
No log	23.0	92	0.7908	0.4899	0.7908	0.8892
No log	24.0	96	0.7140	0.5570	0.7140	0.8450
No log	25.0	100	0.7463	0.5830	0.7463	0.8639
No log	26.0	104	0.9915	0.4698	0.9915	0.9957
No log	27.0	108	0.7426	0.5690	0.7426	0.8617
No log	28.0	112	0.9072	0.4594	0.9072	0.9525
No log	29.0	116	0.8120	0.5524	0.8120	0.9011
No log	30.0	120	0.7974	0.5378	0.7974	0.8930
No log	31.0	124	0.7464	0.5730	0.7464	0.8639
No log	32.0	128	0.8870	0.4888	0.8870	0.9418
No log	33.0	132	0.6822	0.5691	0.6822	0.8260
No log	34.0	136	0.7161	0.5598	0.7161	0.8462
No log	35.0	140	0.7620	0.5601	0.7620	0.8729
No log	36.0	144	0.7838	0.5234	0.7838	0.8853
No log	37.0	148	0.6863	0.5419	0.6863	0.8285
No log	38.0	152	0.8219	0.4779	0.8219	0.9066
No log	39.0	156	0.7735	0.5558	0.7735	0.8795
No log	40.0	160	0.7589	0.5434	0.7589	0.8712
No log	41.0	164	0.7035	0.5803	0.7035	0.8388
No log	42.0	168	0.7072	0.5262	0.7072	0.8410
No log	43.0	172	0.7080	0.5304	0.7080	0.8414
No log	44.0	176	0.7356	0.5491	0.7356	0.8576
No log	45.0	180	0.7555	0.5498	0.7555	0.8692

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold4

Version3ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold4