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	9.5665	-0.0002	9.5639	3.0926
No log	2.0	6	7.9443	0.0	7.9417	2.8181
No log	3.0	9	5.5606	0.0242	5.5586	2.3577
No log	4.0	12	3.9498	0.0	3.9476	1.9868
No log	5.0	15	2.5262	0.0486	2.5244	1.5888
No log	6.0	18	2.0098	0.0468	2.0083	1.4171
No log	7.0	21	1.1353	0.0211	1.1338	1.0648
No log	8.0	24	0.9185	0.0380	0.9171	0.9577
No log	9.0	27	0.9231	0.1894	0.9219	0.9601
No log	10.0	30	0.7927	0.3914	0.7915	0.8897
No log	11.0	33	0.7249	0.3987	0.7237	0.8507
No log	12.0	36	0.7568	0.4102	0.7556	0.8692
No log	13.0	39	0.6798	0.4532	0.6786	0.8238
No log	14.0	42	0.7186	0.4578	0.7173	0.8469
No log	15.0	45	0.6281	0.5190	0.6269	0.7918
No log	16.0	48	1.0585	0.3684	1.0569	1.0280
No log	17.0	51	0.5810	0.4960	0.5798	0.7615
No log	18.0	54	0.6444	0.4900	0.6432	0.8020
No log	19.0	57	0.7019	0.4599	0.7005	0.8369
No log	20.0	60	0.7698	0.4511	0.7682	0.8765
No log	21.0	63	0.6825	0.5128	0.6812	0.8253
No log	22.0	66	0.7889	0.4726	0.7874	0.8873
No log	23.0	69	0.7330	0.5280	0.7317	0.8554
No log	24.0	72	0.8065	0.4637	0.8050	0.8972
No log	25.0	75	0.7366	0.4822	0.7351	0.8574
No log	26.0	78	0.7609	0.4906	0.7594	0.8714
No log	27.0	81	0.8897	0.4594	0.8880	0.9424
No log	28.0	84	0.9524	0.5193	0.9510	0.9752
No log	29.0	87	0.8805	0.4545	0.8789	0.9375
No log	30.0	90	0.8449	0.4499	0.8433	0.9183
No log	31.0	93	0.8234	0.4865	0.8221	0.9067
No log	32.0	96	0.7931	0.4455	0.7916	0.8897
No log	33.0	99	0.8567	0.4930	0.8555	0.9250
No log	34.0	102	0.9513	0.4204	0.9497	0.9745
No log	35.0	105	0.8008	0.4746	0.7994	0.8941
No log	36.0	108	0.8078	0.4444	0.8063	0.8979
No log	37.0	111	0.8148	0.4687	0.8134	0.9019
No log	38.0	114	0.8729	0.4287	0.8713	0.9334
No log	39.0	117	0.8580	0.4646	0.8565	0.9255
No log	40.0	120	0.8130	0.4455	0.8114	0.9008
No log	41.0	123	0.7733	0.4934	0.7720	0.8786
No log	42.0	126	0.7777	0.4840	0.7763	0.8811
No log	43.0	129	0.7924	0.5070	0.7914	0.8896

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV15_k3_task1_organization_k3_k3_fold1

ASAP_FineTuningBERT_AugV15_k3_task1_organization_k3_k3_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV15_k3_task1_organization_k3_k3_fold1