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	10.9466	0.0012	10.9443	3.3082
No log	2.0	6	8.5790	0.0	8.5773	2.9287
No log	3.0	9	5.6274	0.0514	5.6261	2.3719
No log	4.0	12	3.2826	0.0038	3.2814	1.8115
No log	5.0	15	2.1859	0.1091	2.1853	1.4783
No log	6.0	18	1.2761	0.0365	1.2756	1.1294
No log	7.0	21	1.2717	0.0266	1.2709	1.1273
No log	8.0	24	1.0625	0.0051	1.0618	1.0304
No log	9.0	27	1.1966	-0.0398	1.1958	1.0935
No log	10.0	30	1.0219	0.0967	1.0214	1.0107
No log	11.0	33	0.7934	0.3740	0.7933	0.8907
No log	12.0	36	0.9774	0.2688	0.9775	0.9887
No log	13.0	39	0.9335	0.3465	0.9334	0.9661
No log	14.0	42	0.7323	0.3816	0.7322	0.8557
No log	15.0	45	0.7059	0.3258	0.7061	0.8403
No log	16.0	48	0.6676	0.3520	0.6678	0.8172
No log	17.0	51	0.7724	0.3256	0.7724	0.8789
No log	18.0	54	0.8829	0.3031	0.8826	0.9395
No log	19.0	57	0.6606	0.4707	0.6605	0.8127
No log	20.0	60	1.0001	0.2586	0.9996	0.9998
No log	21.0	63	0.6579	0.4892	0.6577	0.8110
No log	22.0	66	0.7789	0.4129	0.7787	0.8824
No log	23.0	69	0.6410	0.5212	0.6410	0.8006
No log	24.0	72	0.8928	0.3672	0.8925	0.9447
No log	25.0	75	0.7311	0.4989	0.7307	0.8548
No log	26.0	78	0.7222	0.4805	0.7220	0.8497
No log	27.0	81	0.6112	0.5484	0.6112	0.7818
No log	28.0	84	0.7634	0.4562	0.7634	0.8737
No log	29.0	87	0.5697	0.5907	0.5696	0.7547
No log	30.0	90	0.6334	0.5482	0.6333	0.7958
No log	31.0	93	0.7408	0.4824	0.7413	0.8610
No log	32.0	96	0.7660	0.4543	0.7663	0.8754
No log	33.0	99	0.5719	0.5609	0.5718	0.7562
No log	34.0	102	0.6498	0.5550	0.6498	0.8061
No log	35.0	105	0.7372	0.4807	0.7376	0.8588
No log	36.0	108	0.6294	0.5738	0.6293	0.7933
No log	37.0	111	0.6593	0.5520	0.6594	0.8120
No log	38.0	114	0.7579	0.4966	0.7583	0.8708
No log	39.0	117	0.7885	0.4744	0.7891	0.8883
No log	40.0	120	0.6676	0.5398	0.6678	0.8172
No log	41.0	123	0.6750	0.5552	0.6752	0.8217
No log	42.0	126	0.7076	0.5562	0.7078	0.8413
No log	43.0	129	0.7397	0.5141	0.7400	0.8603
No log	44.0	132	0.6549	0.5512	0.6550	0.8093
No log	45.0	135	0.6705	0.5545	0.6706	0.8189
No log	46.0	138	0.7075	0.5400	0.7077	0.8412
No log	47.0	141	0.6422	0.5751	0.6422	0.8014
No log	48.0	144	0.6533	0.5578	0.6534	0.8083
No log	49.0	147	0.7078	0.5621	0.7080	0.8414

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold3

ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV11_k3_task1_organization_k3_k3_fold3