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	11.2351	-0.0010	11.2329	3.3515
No log	2.0	6	9.4784	0.0	9.4765	3.0784
No log	3.0	9	8.1394	0.0	8.1376	2.8527
No log	4.0	12	7.7318	0.0	7.7301	2.7803
No log	5.0	15	6.7929	0.0	6.7913	2.6060
No log	6.0	18	5.0614	0.0038	5.0602	2.2495
No log	7.0	21	4.0932	0.0	4.0922	2.0229
No log	8.0	24	2.3620	0.1844	2.3613	1.5366
No log	9.0	27	1.9032	0.0765	1.9027	1.3794
No log	10.0	30	1.1589	0.0	1.1584	1.0763
No log	11.0	33	0.9273	0.2642	0.9270	0.9628
No log	12.0	36	0.8065	0.1931	0.8063	0.8979
No log	13.0	39	0.8496	0.0570	0.8495	0.9217
No log	14.0	42	1.0147	0.0157	1.0147	1.0073
No log	15.0	45	1.1582	0.2489	1.1582	1.0762
No log	16.0	48	1.4163	0.1974	1.4163	1.1901
No log	17.0	51	1.2437	0.2922	1.2434	1.1151
No log	18.0	54	0.7787	0.4031	0.7782	0.8821
No log	19.0	57	0.5868	0.5250	0.5861	0.7656
No log	20.0	60	0.6087	0.5949	0.6079	0.7797
No log	21.0	63	0.6080	0.5853	0.6074	0.7794
No log	22.0	66	0.8018	0.5922	0.8009	0.8950
No log	23.0	69	0.6395	0.5986	0.6392	0.7995
No log	24.0	72	0.8783	0.6124	0.8775	0.9367
No log	25.0	75	0.6678	0.6398	0.6675	0.8170
No log	26.0	78	0.7531	0.6295	0.7524	0.8674
No log	27.0	81	0.6553	0.6340	0.6546	0.8091
No log	28.0	84	0.7365	0.6176	0.7358	0.8578
No log	29.0	87	0.6766	0.6290	0.6758	0.8221
No log	30.0	90	0.7102	0.6331	0.7093	0.8422
No log	31.0	93	0.7260	0.6129	0.7252	0.8516
No log	32.0	96	0.7027	0.6323	0.7020	0.8378
No log	33.0	99	0.7967	0.6206	0.7957	0.8920
No log	34.0	102	0.6870	0.6301	0.6862	0.8284
No log	35.0	105	0.7719	0.6040	0.7710	0.8781
No log	36.0	108	0.7559	0.5939	0.7554	0.8691
No log	37.0	111	0.7416	0.6135	0.7409	0.8608
No log	38.0	114	0.6672	0.6240	0.6663	0.8163
No log	39.0	117	0.6954	0.6094	0.6945	0.8334
No log	40.0	120	0.6856	0.6128	0.6847	0.8275
No log	41.0	123	0.6766	0.6290	0.6759	0.8221
No log	42.0	126	0.6396	0.6380	0.6390	0.7994
No log	43.0	129	0.7354	0.6373	0.7345	0.8570
No log	44.0	132	0.7464	0.6286	0.7454	0.8634
No log	45.0	135	0.6029	0.6302	0.6022	0.7760

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version_weird_ASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold3

Version_weird_ASAP_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/
Version_weird_ASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold3