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	3	11.1386	0.0012	11.1363	3.3371
No log	2.0	6	9.3462	0.0	9.3444	3.0569
No log	3.0	9	7.1567	0.0	7.1552	2.6749
No log	4.0	12	4.3599	0.0134	4.3588	2.0878
No log	5.0	15	2.7549	0.0344	2.7539	1.6595
No log	6.0	18	1.9231	0.0866	1.9225	1.3865
No log	7.0	21	1.1442	0.0365	1.1436	1.0694
No log	8.0	24	0.9010	0.2977	0.9007	0.9490
No log	9.0	27	0.8572	0.0880	0.8570	0.9257
No log	10.0	30	0.9062	0.0570	0.9061	0.9519
No log	11.0	33	1.1663	0.0414	1.1662	1.0799
No log	12.0	36	1.3629	0.1871	1.3630	1.1675
No log	13.0	39	1.7284	0.1324	1.7287	1.3148
No log	14.0	42	1.8363	0.1585	1.8366	1.3552
No log	15.0	45	1.2855	0.3327	1.2856	1.1338
No log	16.0	48	0.7345	0.5114	0.7342	0.8568
No log	17.0	51	0.7056	0.5083	0.7049	0.8396
No log	18.0	54	0.6857	0.5826	0.6853	0.8278
No log	19.0	57	0.6785	0.5622	0.6782	0.8235
No log	20.0	60	0.6715	0.6401	0.6713	0.8193
No log	21.0	63	0.8130	0.6352	0.8127	0.9015
No log	22.0	66	0.7542	0.6070	0.7540	0.8684
No log	23.0	69	0.7496	0.6522	0.7494	0.8657
No log	24.0	72	0.7032	0.6435	0.7031	0.8385
No log	25.0	75	0.6340	0.6481	0.6340	0.7962
No log	26.0	78	0.8829	0.6149	0.8826	0.9394
No log	27.0	81	0.7689	0.6495	0.7687	0.8768
No log	28.0	84	0.6941	0.6601	0.6940	0.8330
No log	29.0	87	0.6383	0.6734	0.6381	0.7988
No log	30.0	90	0.7013	0.6557	0.7011	0.8373
No log	31.0	93	0.8532	0.6107	0.8529	0.9235
No log	32.0	96	0.6326	0.6383	0.6325	0.7953
No log	33.0	99	0.6159	0.6430	0.6158	0.7847
No log	34.0	102	0.8582	0.6089	0.8578	0.9262
No log	35.0	105	0.6040	0.6668	0.6038	0.7770
No log	36.0	108	0.6038	0.6571	0.6036	0.7769
No log	37.0	111	0.7520	0.6470	0.7516	0.8669
No log	38.0	114	0.5998	0.6431	0.5996	0.7744
No log	39.0	117	0.8145	0.6202	0.8141	0.9023
No log	40.0	120	0.7404	0.6397	0.7401	0.8603
No log	41.0	123	0.5242	0.6635	0.5240	0.7239
No log	42.0	126	0.7142	0.6386	0.7139	0.8449
No log	43.0	129	0.5794	0.6454	0.5792	0.7611
No log	44.0	132	0.5988	0.6460	0.5986	0.7737
No log	45.0	135	0.5952	0.6412	0.5951	0.7714
No log	46.0	138	0.6966	0.6617	0.6963	0.8345
No log	47.0	141	0.5983	0.6571	0.5981	0.7734
No log	48.0	144	0.7096	0.6563	0.7093	0.8422
No log	49.0	147	0.6260	0.6496	0.6258	0.7910

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3

Version2ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3