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	4	9.8321	0.0	9.8301	3.1353
No log	2.0	8	7.8466	0.0	7.8451	2.8009
No log	3.0	12	5.1691	0.0139	5.1677	2.2733
No log	4.0	16	3.2000	0.0	3.1991	1.7886
No log	5.0	20	2.0661	0.0904	2.0654	1.4371
No log	6.0	24	1.3530	0.0266	1.3524	1.1629
No log	7.0	28	1.8633	0.0209	1.8626	1.3648
No log	8.0	32	0.8967	0.1865	0.8965	0.9468
No log	9.0	36	0.8994	0.2779	0.8996	0.9485
No log	10.0	40	0.7110	0.3717	0.7114	0.8434
No log	11.0	44	0.7413	0.4156	0.7411	0.8609
No log	12.0	48	1.2436	0.1284	1.2447	1.1157
No log	13.0	52	0.9338	0.2723	0.9350	0.9670
No log	14.0	56	0.7109	0.4294	0.7106	0.8430
No log	15.0	60	0.7371	0.3657	0.7386	0.8594
No log	16.0	64	0.7887	0.3502	0.7903	0.8890
No log	17.0	68	0.5655	0.5267	0.5656	0.7520
No log	18.0	72	0.5784	0.5584	0.5786	0.7606
No log	19.0	76	0.6533	0.5034	0.6544	0.8090
No log	20.0	80	0.5971	0.6295	0.5976	0.7730
No log	21.0	84	0.6660	0.5804	0.6666	0.8165
No log	22.0	88	0.6099	0.6330	0.6104	0.7813
No log	23.0	92	0.6394	0.5764	0.6403	0.8002
No log	24.0	96	0.6809	0.5758	0.6813	0.8254
No log	25.0	100	0.6497	0.6087	0.6503	0.8064
No log	26.0	104	0.6846	0.5725	0.6852	0.8278
No log	27.0	108	0.7125	0.5322	0.7135	0.8447
No log	28.0	112	0.6318	0.5925	0.6317	0.7948
No log	29.0	116	0.6839	0.5610	0.6840	0.8271
No log	30.0	120	0.6969	0.5808	0.6977	0.8353
No log	31.0	124	0.6883	0.5988	0.6883	0.8297
No log	32.0	128	0.6791	0.5715	0.6797	0.8244
No log	33.0	132	0.6669	0.6066	0.6670	0.8167
No log	34.0	136	0.7140	0.5824	0.7145	0.8453
No log	35.0	140	0.6968	0.5813	0.6969	0.8348
No log	36.0	144	0.7065	0.5769	0.7070	0.8409
No log	37.0	148	0.6829	0.5985	0.6831	0.8265
No log	38.0	152	0.6776	0.5742	0.6781	0.8235
No log	39.0	156	0.6600	0.6051	0.6601	0.8125
No log	40.0	160	0.6905	0.5720	0.6912	0.8314
No log	41.0	164	0.7166	0.6148	0.7166	0.8465
No log	42.0	168	0.7009	0.5909	0.7013	0.8375
No log	43.0	172	0.6964	0.5791	0.6968	0.8348
No log	44.0	176	0.7185	0.5964	0.7187	0.8478
No log	45.0	180	0.7610	0.5462	0.7619	0.8729
No log	46.0	184	0.7105	0.5678	0.7113	0.8434
No log	47.0	188	0.6757	0.6216	0.6757	0.8220
No log	48.0	192	0.6761	0.5888	0.6766	0.8226
No log	49.0	196	0.6777	0.5854	0.6783	0.8236
No log	50.0	200	0.7615	0.6024	0.7615	0.8727
No log	51.0	204	0.7039	0.5912	0.7044	0.8393
No log	52.0	208	0.6650	0.5959	0.6654	0.8157

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV21_k3_task1_organization_k3_k3_fold3

ASAP_FineTuningBERT_AugV21_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_AugV21_k3_task1_organization_k3_k3_fold3