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	8	5.3103	0.0137	5.3107	2.3045
No log	2.0	16	1.9866	0.0602	1.9871	1.4096
No log	3.0	24	2.3103	0.1302	2.3108	1.5201
No log	4.0	32	2.0644	0.1550	2.0647	1.4369
No log	5.0	40	1.6916	0.1110	1.6920	1.3008
No log	6.0	48	1.3171	0.1088	1.3174	1.1478
No log	7.0	56	1.1579	0.0970	1.1582	1.0762
No log	8.0	64	1.5085	0.1962	1.5089	1.2284
No log	9.0	72	0.9978	0.0850	0.9981	0.9990
No log	10.0	80	1.1489	0.1577	1.1491	1.0720
No log	11.0	88	0.7871	0.2676	0.7874	0.8874
No log	12.0	96	0.6652	0.4790	0.6654	0.8157
No log	13.0	104	0.6658	0.3540	0.6661	0.8162
No log	14.0	112	0.5977	0.4759	0.5976	0.7730
No log	15.0	120	0.6005	0.4899	0.6003	0.7748
No log	16.0	128	0.6208	0.4743	0.6206	0.7878
No log	17.0	136	0.6027	0.4742	0.6023	0.7761
No log	18.0	144	0.6182	0.4544	0.6179	0.7861
No log	19.0	152	0.6645	0.4861	0.6640	0.8149
No log	20.0	160	0.7520	0.5489	0.7515	0.8669
No log	21.0	168	0.6935	0.5392	0.6929	0.8324
No log	22.0	176	0.7686	0.49	0.7679	0.8763
No log	23.0	184	0.8946	0.5465	0.8935	0.9452
No log	24.0	192	0.6301	0.5317	0.6294	0.7933
No log	25.0	200	0.7330	0.5133	0.7326	0.8559
No log	26.0	208	0.8381	0.4649	0.8371	0.9149
No log	27.0	216	0.8893	0.5288	0.8879	0.9423
No log	28.0	224	0.9630	0.4707	0.9621	0.9808
No log	29.0	232	0.9567	0.4986	0.9558	0.9776
No log	30.0	240	0.8335	0.5271	0.8328	0.9126
No log	31.0	248	0.9583	0.5061	0.9575	0.9785
No log	32.0	256	0.9996	0.5002	0.9986	0.9993
No log	33.0	264	0.9789	0.5275	0.9777	0.9888
No log	34.0	272	0.7826	0.5717	0.7819	0.8842
No log	35.0	280	1.1789	0.4500	1.1778	1.0853
No log	36.0	288	0.9651	0.5402	0.9643	0.9820
No log	37.0	296	0.8714	0.5362	0.8708	0.9332
No log	38.0	304	1.1388	0.4975	1.1378	1.0667
No log	39.0	312	0.8149	0.5357	0.8144	0.9025
No log	40.0	320	1.2785	0.4494	1.2774	1.1302
No log	41.0	328	0.8902	0.5356	0.8895	0.9431
No log	42.0	336	0.9798	0.5409	0.9790	0.9894
No log	43.0	344	1.0783	0.5057	1.0773	1.0379
No log	44.0	352	0.8153	0.5519	0.8148	0.9027
No log	45.0	360	1.0146	0.5258	1.0138	1.0069
No log	46.0	368	0.9352	0.5330	0.9346	0.9667
No log	47.0	376	1.1869	0.4795	1.1861	1.0891
No log	48.0	384	0.8145	0.5473	0.8140	0.9022
No log	49.0	392	1.2098	0.4809	1.2088	1.0995
No log	50.0	400	1.0550	0.4994	1.0544	1.0268
No log	51.0	408	1.0551	0.4922	1.0545	1.0269
No log	52.0	416	1.1184	0.4915	1.1178	1.0573
No log	53.0	424	1.0350	0.4822	1.0344	1.0171
No log	54.0	432	0.9969	0.4987	0.9964	0.9982

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV15_k10_task1_organization_k10_k10_fold2

ASAP_FineTuningBERT_AugV15_k10_task1_organization_k10_k10_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV15_k10_task1_organization_k10_k10_fold2