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	8.3324	0.0036	8.3324	2.8866
No log	2.0	12	5.2217	0.0164	5.2217	2.2851
No log	3.0	18	2.7018	0.0077	2.7018	1.6437
No log	4.0	24	1.5105	0.0644	1.5105	1.2290
No log	5.0	30	1.5721	0.0418	1.5721	1.2538
No log	6.0	36	1.1450	0.0518	1.1450	1.0700
No log	7.0	42	1.5604	0.0518	1.5604	1.2492
No log	8.0	48	0.9704	0.0944	0.9704	0.9851
No log	9.0	54	1.1032	0.1355	1.1032	1.0503
No log	10.0	60	1.1773	0.1328	1.1773	1.0850
No log	11.0	66	1.0335	0.3705	1.0335	1.0166
No log	12.0	72	0.7321	0.2807	0.7321	0.8556
No log	13.0	78	0.7622	0.4584	0.7622	0.8730
No log	14.0	84	1.1408	0.3104	1.1408	1.0681
No log	15.0	90	0.7237	0.4682	0.7237	0.8507
No log	16.0	96	0.7400	0.4790	0.7400	0.8602
No log	17.0	102	0.8926	0.4305	0.8926	0.9448
No log	18.0	108	0.8138	0.5016	0.8138	0.9021
No log	19.0	114	0.8881	0.4679	0.8881	0.9424
No log	20.0	120	0.8518	0.4894	0.8518	0.9229
No log	21.0	126	0.9906	0.4341	0.9906	0.9953
No log	22.0	132	0.8218	0.4527	0.8218	0.9065
No log	23.0	138	0.9269	0.4648	0.9269	0.9627
No log	24.0	144	0.9695	0.4735	0.9695	0.9846
No log	25.0	150	0.8574	0.4448	0.8574	0.9259
No log	26.0	156	0.8895	0.4629	0.8895	0.9431
No log	27.0	162	0.8601	0.4678	0.8601	0.9274
No log	28.0	168	0.7612	0.4966	0.7612	0.8725
No log	29.0	174	0.8959	0.5032	0.8959	0.9465
No log	30.0	180	0.8192	0.5133	0.8192	0.9051
No log	31.0	186	0.8412	0.4947	0.8412	0.9172
No log	32.0	192	0.8211	0.4695	0.8211	0.9062
No log	33.0	198	0.8079	0.5018	0.8079	0.8988
No log	34.0	204	0.7896	0.5032	0.7896	0.8886
No log	35.0	210	0.7608	0.4973	0.7608	0.8722
No log	36.0	216	0.8002	0.4701	0.8002	0.8945
No log	37.0	222	0.8223	0.4702	0.8223	0.9068
No log	38.0	228	0.8048	0.5001	0.8048	0.8971
No log	39.0	234	0.7962	0.4783	0.7962	0.8923
No log	40.0	240	0.8103	0.4770	0.8103	0.9002
No log	41.0	246	0.8205	0.4713	0.8205	0.9058
No log	42.0	252	0.8560	0.4541	0.8560	0.9252
No log	43.0	258	0.8491	0.4669	0.8491	0.9215
No log	44.0	264	0.7902	0.4827	0.7902	0.8889
No log	45.0	270	0.7972	0.4609	0.7972	0.8928
No log	46.0	276	0.8435	0.4764	0.8435	0.9184
No log	47.0	282	0.8825	0.4639	0.8825	0.9394
No log	48.0	288	0.8321	0.4801	0.8321	0.9122
No log	49.0	294	0.8237	0.4739	0.8237	0.9076
No log	50.0	300	0.8409	0.4724	0.8409	0.9170

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold0

Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV6_k7_task1_organization_k7_k7_fold0