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	8.0637	0.0	8.0621	2.8394
No log	2.0	6	5.0585	0.0193	5.0573	2.2488
No log	3.0	9	3.3847	0.0076	3.3837	1.8395
No log	4.0	12	2.3812	0.1584	2.3803	1.5428
No log	5.0	15	1.6450	0.0391	1.6443	1.2823
No log	6.0	18	1.1523	0.0202	1.1517	1.0732
No log	7.0	21	0.8913	0.3293	0.8908	0.9438
No log	8.0	24	0.8070	0.2421	0.8066	0.8981
No log	9.0	27	0.8825	0.0567	0.8821	0.9392
No log	10.0	30	0.9683	0.0567	0.9681	0.9839
No log	11.0	33	1.1070	0.2563	1.1069	1.0521
No log	12.0	36	1.2874	0.2406	1.2874	1.1346
No log	13.0	39	1.1951	0.3154	1.1950	1.0932
No log	14.0	42	0.9305	0.4082	0.9304	0.9646
No log	15.0	45	0.7123	0.5560	0.7121	0.8438
No log	16.0	48	0.7518	0.5385	0.7516	0.8670
No log	17.0	51	1.2164	0.4078	1.2162	1.1028
No log	18.0	54	0.8109	0.6009	0.8106	0.9004
No log	19.0	57	0.5904	0.6115	0.5902	0.7682
No log	20.0	60	0.7086	0.6252	0.7085	0.8417
No log	21.0	63	0.6472	0.6100	0.6471	0.8044
No log	22.0	66	0.9097	0.5811	0.9096	0.9537
No log	23.0	69	0.7039	0.6490	0.7037	0.8389
No log	24.0	72	0.7351	0.6071	0.7348	0.8572
No log	25.0	75	0.8890	0.5886	0.8885	0.9426
No log	26.0	78	0.6632	0.6234	0.6629	0.8142
No log	27.0	81	0.7493	0.5986	0.7489	0.8654
No log	28.0	84	0.7204	0.6136	0.7200	0.8485
No log	29.0	87	0.6520	0.5967	0.6518	0.8073
No log	30.0	90	0.9093	0.5684	0.9088	0.9533
No log	31.0	93	0.6101	0.6165	0.6098	0.7809
No log	32.0	96	0.6101	0.6162	0.6098	0.7809
No log	33.0	99	0.6807	0.6242	0.6802	0.8248
No log	34.0	102	0.6537	0.6036	0.6533	0.8083
No log	35.0	105	0.7581	0.6181	0.7575	0.8704
No log	36.0	108	0.7173	0.6117	0.7167	0.8466
No log	37.0	111	0.8164	0.5936	0.8157	0.9032
No log	38.0	114	0.7554	0.6089	0.7548	0.8688
No log	39.0	117	0.8139	0.6074	0.8133	0.9018
No log	40.0	120	0.7315	0.6137	0.7309	0.8549
No log	41.0	123	0.7361	0.6251	0.7355	0.8576
No log	42.0	126	0.7724	0.5992	0.7718	0.8785
No log	43.0	129	0.6398	0.6437	0.6393	0.7996

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold3

Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold3