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	10.2652	0.0030	10.2635	3.2037
No log	2.0	4	6.8951	0.0	6.8937	2.6256
No log	3.0	6	5.0392	0.0100	5.0379	2.2445
No log	4.0	8	3.8289	0.0	3.8279	1.9565
No log	5.0	10	3.0073	0.0	3.0064	1.7339
No log	6.0	12	2.3830	0.0882	2.3823	1.5435
No log	7.0	14	1.6551	0.0266	1.6545	1.2863
No log	8.0	16	1.3462	0.0102	1.3455	1.1600
No log	9.0	18	1.0442	0.0102	1.0438	1.0217
No log	10.0	20	0.8914	0.2651	0.8910	0.9439
No log	11.0	22	0.7554	0.3336	0.7551	0.8690
No log	12.0	24	0.6955	0.4463	0.6952	0.8338
No log	13.0	26	0.7784	0.3879	0.7781	0.8821
No log	14.0	28	0.6748	0.4783	0.6746	0.8214
No log	15.0	30	0.5357	0.5677	0.5357	0.7319
No log	16.0	32	0.5469	0.5641	0.5469	0.7395
No log	17.0	34	0.6326	0.5413	0.6327	0.7954
No log	18.0	36	0.7766	0.4913	0.7767	0.8813
No log	19.0	38	0.6075	0.5457	0.6077	0.7795
No log	20.0	40	0.5430	0.6537	0.5431	0.7370
No log	21.0	42	0.5516	0.6380	0.5517	0.7428
No log	22.0	44	0.5375	0.6577	0.5377	0.7333
No log	23.0	46	0.5468	0.6434	0.5470	0.7396
No log	24.0	48	0.5548	0.6368	0.5550	0.7449
No log	25.0	50	0.5907	0.6097	0.5908	0.7686
No log	26.0	52	0.6466	0.6411	0.6467	0.8042
No log	27.0	54	0.6257	0.6569	0.6258	0.7911
No log	28.0	56	0.6969	0.5907	0.6970	0.8348
No log	29.0	58	0.6903	0.6388	0.6904	0.8309
No log	30.0	60	0.7033	0.6315	0.7035	0.8387
No log	31.0	62	0.7754	0.5457	0.7755	0.8806
No log	32.0	64	0.7446	0.6313	0.7447	0.8630
No log	33.0	66	0.7382	0.6239	0.7383	0.8592
No log	34.0	68	0.6894	0.6031	0.6895	0.8304
No log	35.0	70	0.7113	0.6306	0.7114	0.8435
No log	36.0	72	0.6764	0.6383	0.6765	0.8225
No log	37.0	74	0.6486	0.6047	0.6487	0.8054
No log	38.0	76	0.7171	0.6245	0.7172	0.8469
No log	39.0	78	0.7031	0.6286	0.7032	0.8386
No log	40.0	80	0.6731	0.5876	0.6732	0.8205
No log	41.0	82	0.6793	0.6433	0.6794	0.8242
No log	42.0	84	0.6999	0.6341	0.7000	0.8366

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3_ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

Version3_ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3_ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3