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	8.9633	0.0	8.9633	2.9939
No log	2.0	4	7.5680	0.0	7.5680	2.7510
No log	3.0	6	6.8466	0.0	6.8466	2.6166
No log	4.0	8	5.9456	0.0264	5.9456	2.4384
No log	5.0	10	5.1672	0.0115	5.1672	2.2732
No log	6.0	12	4.3710	0.0039	4.3710	2.0907
No log	7.0	14	3.7036	0.0	3.7036	1.9245
No log	8.0	16	2.8731	0.0	2.8731	1.6950
No log	9.0	18	2.2381	0.0751	2.2381	1.4960
No log	10.0	20	1.7382	0.0316	1.7382	1.3184
No log	11.0	22	1.3755	0.0316	1.3755	1.1728
No log	12.0	24	1.0985	0.0316	1.0985	1.0481
No log	13.0	26	0.9137	0.0316	0.9137	0.9559
No log	14.0	28	0.7795	0.2700	0.7795	0.8829
No log	15.0	30	0.7202	0.2266	0.7202	0.8486
No log	16.0	32	0.6637	0.2618	0.6637	0.8147
No log	17.0	34	0.7000	0.1932	0.7000	0.8367
No log	18.0	36	0.6384	0.2478	0.6384	0.7990
No log	19.0	38	0.6835	0.2620	0.6835	0.8267
No log	20.0	40	0.5346	0.3824	0.5346	0.7312
No log	21.0	42	0.7525	0.4837	0.7525	0.8675
No log	22.0	44	0.6242	0.5088	0.6242	0.7901
No log	23.0	46	0.5186	0.5730	0.5186	0.7201
No log	24.0	48	0.5910	0.5793	0.5910	0.7688
No log	25.0	50	0.6322	0.6044	0.6322	0.7951
No log	26.0	52	0.7485	0.5882	0.7485	0.8652
No log	27.0	54	0.5863	0.6380	0.5863	0.7657
No log	28.0	56	0.4526	0.6627	0.4526	0.6728
No log	29.0	58	1.0030	0.5075	1.0030	1.0015
No log	30.0	60	0.8851	0.5533	0.8851	0.9408
No log	31.0	62	0.4856	0.6395	0.4856	0.6968
No log	32.0	64	0.4967	0.6689	0.4967	0.7048
No log	33.0	66	0.5454	0.6538	0.5454	0.7385
No log	34.0	68	0.4535	0.6453	0.4535	0.6734
No log	35.0	70	0.4777	0.6415	0.4777	0.6912
No log	36.0	72	0.4739	0.6452	0.4739	0.6884
No log	37.0	74	0.5951	0.6340	0.5951	0.7714
No log	38.0	76	0.5077	0.6406	0.5077	0.7125
No log	39.0	78	0.4976	0.6390	0.4976	0.7054
No log	40.0	80	0.6824	0.6089	0.6824	0.8261
No log	41.0	82	0.4931	0.6230	0.4931	0.7022
No log	42.0	84	0.5013	0.6303	0.5013	0.7080
No log	43.0	86	0.5711	0.6256	0.5711	0.7557
No log	44.0	88	0.4876	0.6300	0.4876	0.6982
No log	45.0	90	0.4928	0.6377	0.4928	0.7020
No log	46.0	92	0.6076	0.6165	0.6076	0.7795
No log	47.0	94	0.5265	0.6449	0.5265	0.7256
No log	48.0	96	0.5043	0.6327	0.5043	0.7102
No log	49.0	98	0.5774	0.6473	0.5774	0.7598
No log	50.0	100	0.5619	0.6487	0.5619	0.7496
No log	51.0	102	0.5783	0.6321	0.5783	0.7604
No log	52.0	104	0.5586	0.6300	0.5586	0.7474

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Version3ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0