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	2	8.3285	0.0079	8.3285	2.8859
No log	2.0	4	5.8414	0.0565	5.8414	2.4169
No log	3.0	6	4.5329	0.0329	4.5329	2.1291
No log	4.0	8	3.7431	0.0329	3.7431	1.9347
No log	5.0	10	3.1934	0.0329	3.1934	1.7870
No log	6.0	12	2.5606	0.1018	2.5606	1.6002
No log	7.0	14	2.1614	0.0748	2.1614	1.4702
No log	8.0	16	1.7424	0.0850	1.7424	1.3200
No log	9.0	18	1.4765	0.0850	1.4765	1.2151
No log	10.0	20	1.2471	0.0850	1.2471	1.1168
No log	11.0	22	1.2534	0.0850	1.2534	1.1195
No log	12.0	24	1.1576	0.0850	1.1576	1.0759
No log	13.0	26	1.3504	0.0949	1.3504	1.1621
No log	14.0	28	1.4371	0.1281	1.4371	1.1988
No log	15.0	30	0.9872	0.1816	0.9872	0.9936
No log	16.0	32	1.0905	0.1162	1.0905	1.0443
No log	17.0	34	0.9929	0.2172	0.9929	0.9964
No log	18.0	36	0.9931	0.2026	0.9931	0.9965
No log	19.0	38	0.9766	0.2483	0.9766	0.9883
No log	20.0	40	0.9092	0.3373	0.9092	0.9535
No log	21.0	42	0.8902	0.2437	0.8902	0.9435
No log	22.0	44	0.8368	0.3606	0.8368	0.9148
No log	23.0	46	0.8126	0.2686	0.8126	0.9014
No log	24.0	48	0.7393	0.3470	0.7393	0.8598
No log	25.0	50	0.7271	0.3402	0.7271	0.8527
No log	26.0	52	0.7409	0.2859	0.7409	0.8608
No log	27.0	54	0.7567	0.3209	0.7567	0.8699
No log	28.0	56	0.7437	0.3267	0.7437	0.8624
No log	29.0	58	0.7511	0.3467	0.7511	0.8666
No log	30.0	60	0.7420	0.4128	0.7420	0.8614
No log	31.0	62	0.7804	0.4543	0.7804	0.8834
No log	32.0	64	0.8129	0.4478	0.8129	0.9016
No log	33.0	66	0.7865	0.4703	0.7865	0.8869
No log	34.0	68	0.8143	0.4711	0.8143	0.9024
No log	35.0	70	0.8254	0.4760	0.8254	0.9085
No log	36.0	72	0.7932	0.4574	0.7932	0.8906
No log	37.0	74	0.8825	0.3884	0.8825	0.9394
No log	38.0	76	0.8537	0.4171	0.8537	0.9239
No log	39.0	78	0.8519	0.3972	0.8519	0.9230
No log	40.0	80	1.0126	0.3648	1.0126	1.0063
No log	41.0	82	1.0934	0.3714	1.0934	1.0456
No log	42.0	84	1.0440	0.3665	1.0440	1.0218
No log	43.0	86	1.0107	0.3740	1.0107	1.0053
No log	44.0	88	1.1709	0.3490	1.1709	1.0821
No log	45.0	90	1.2118	0.3359	1.2118	1.1008
No log	46.0	92	1.0457	0.3945	1.0457	1.0226
No log	47.0	94	0.9952	0.4290	0.9952	0.9976
No log	48.0	96	0.9439	0.4305	0.9439	0.9715
No log	49.0	98	0.8563	0.4378	0.8563	0.9254
No log	50.0	100	0.9042	0.4106	0.9042	0.9509
No log	51.0	102	1.1133	0.3768	1.1133	1.0551
No log	52.0	104	1.1016	0.3762	1.1016	1.0496
No log	53.0	106	0.9290	0.4376	0.9290	0.9639
No log	54.0	108	0.9065	0.4289	0.9065	0.9521
No log	55.0	110	0.9949	0.3567	0.9949	0.9974

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0

Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0