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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	12.2862	0.0	12.2862	3.5052
No log	2.0	2	10.9865	0.0086	10.9865	3.3146
No log	3.0	3	9.8364	0.0018	9.8364	3.1363
No log	4.0	4	8.4744	0.0018	8.4744	2.9111
No log	5.0	5	7.7600	0.0018	7.7600	2.7857
No log	6.0	6	7.1786	0.0	7.1786	2.6793
No log	7.0	7	6.4089	-0.0005	6.4089	2.5316
No log	8.0	8	5.4455	0.0240	5.4455	2.3336
No log	9.0	9	4.8876	0.0089	4.8876	2.2108
No log	10.0	10	4.6277	0.0040	4.6277	2.1512
No log	11.0	11	4.2262	0.0040	4.2262	2.0558
No log	12.0	12	3.5977	0.0040	3.5977	1.8968
No log	13.0	13	3.2975	0.0040	3.2975	1.8159
No log	14.0	14	2.9388	0.0040	2.9388	1.7143
No log	15.0	15	2.7398	0.0040	2.7398	1.6552
No log	16.0	16	2.4823	0.0015	2.4823	1.5755
No log	17.0	17	2.0903	0.0820	2.0903	1.4458
No log	18.0	18	1.9287	0.1195	1.9287	1.3888
No log	19.0	19	1.6285	0.0407	1.6285	1.2761
No log	20.0	20	1.4676	0.0420	1.4676	1.2114
No log	21.0	21	1.2816	0.0420	1.2816	1.1321
No log	22.0	22	1.2497	0.0420	1.2497	1.1179
No log	23.0	23	1.0805	0.0212	1.0805	1.0395
No log	24.0	24	0.9897	0.0212	0.9897	0.9948
No log	25.0	25	0.9403	0.0223	0.9403	0.9697
No log	26.0	26	0.8403	0.3122	0.8403	0.9167
No log	27.0	27	0.7917	0.3182	0.7917	0.8898
No log	28.0	28	0.7501	0.3478	0.7501	0.8661
No log	29.0	29	0.7168	0.3559	0.7168	0.8467
No log	30.0	30	0.6977	0.3707	0.6977	0.8353
No log	31.0	31	0.6488	0.4111	0.6488	0.8055
No log	32.0	32	0.6850	0.4241	0.6850	0.8277
No log	33.0	33	0.7032	0.4673	0.7032	0.8386
No log	34.0	34	0.6279	0.5125	0.6279	0.7924
No log	35.0	35	0.6383	0.5368	0.6383	0.7989
No log	36.0	36	0.6827	0.5145	0.6827	0.8263
No log	37.0	37	0.6973	0.5305	0.6973	0.8351
No log	38.0	38	0.7229	0.5194	0.7229	0.8502
No log	39.0	39	0.7407	0.5091	0.7407	0.8606
No log	40.0	40	0.7357	0.5397	0.7357	0.8577
No log	41.0	41	0.7464	0.5443	0.7464	0.8639
No log	42.0	42	0.7820	0.5274	0.7820	0.8843
No log	43.0	43	0.7678	0.5486	0.7678	0.8763
No log	44.0	44	0.7800	0.5471	0.7800	0.8832
No log	45.0	45	0.7877	0.5497	0.7877	0.8875
No log	46.0	46	0.7398	0.5536	0.7398	0.8601
No log	47.0	47	0.7330	0.5644	0.7330	0.8561
No log	48.0	48	0.8148	0.5335	0.8148	0.9027
No log	49.0	49	0.8172	0.5297	0.8172	0.9040
No log	50.0	50	0.7173	0.5564	0.7173	0.8469
No log	51.0	51	0.7117	0.5553	0.7117	0.8437
No log	52.0	52	0.8171	0.4724	0.8171	0.9040
No log	53.0	53	0.8070	0.4930	0.8070	0.8984
No log	54.0	54	0.7009	0.6009	0.7009	0.8372
No log	55.0	55	0.7100	0.5973	0.7100	0.8426
No log	56.0	56	0.8454	0.4743	0.8454	0.9195
No log	57.0	57	0.8507	0.4873	0.8507	0.9224
No log	58.0	58	0.7345	0.5902	0.7345	0.8571
No log	59.0	59	0.7588	0.5823	0.7588	0.8711
No log	60.0	60	0.9046	0.4635	0.9046	0.9511
No log	61.0	61	0.9030	0.4729	0.9030	0.9502
No log	62.0	62	0.7777	0.5772	0.7777	0.8819
No log	63.0	63	0.7916	0.5734	0.7916	0.8897
No log	64.0	64	0.9266	0.4796	0.9266	0.9626
No log	65.0	65	0.9257	0.4865	0.9257	0.9621
No log	66.0	66	0.8102	0.5765	0.8102	0.9001
No log	67.0	67	0.8315	0.5632	0.8315	0.9118
No log	68.0	68	0.9491	0.4558	0.9491	0.9742
No log	69.0	69	0.9451	0.4591	0.9451	0.9721
No log	70.0	70	0.8639	0.5460	0.8639	0.9294
No log	71.0	71	0.8725	0.5488	0.8725	0.9341
No log	72.0	72	0.9668	0.5106	0.9668	0.9833
No log	73.0	73	0.9904	0.5195	0.9904	0.9952
No log	74.0	74	0.9313	0.5363	0.9313	0.9651
No log	75.0	75	0.9649	0.5318	0.9649	0.9823
No log	76.0	76	1.0708	0.4829	1.0708	1.0348
No log	77.0	77	1.0722	0.4661	1.0722	1.0355
No log	78.0	78	1.0112	0.5060	1.0112	1.0056
No log	79.0	79	1.0203	0.4846	1.0203	1.0101
No log	80.0	80	1.0544	0.4584	1.0544	1.0268
No log	81.0	81	1.0821	0.4965	1.0821	1.0403
No log	82.0	82	1.1454	0.4758	1.1454	1.0702
No log	83.0	83	1.2493	0.4281	1.2493	1.1177
No log	84.0	84	1.2814	0.4677	1.2814	1.1320

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold4

Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold4