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	13.4559	0.0	13.4562	3.6683
No log	2.0	4	10.2579	0.0036	10.2583	3.2029
No log	3.0	6	9.0854	0.0	9.0859	3.0143
No log	4.0	8	7.0241	-0.0148	7.0240	2.6503
No log	5.0	10	5.0639	0.0131	5.0643	2.2504
No log	6.0	12	3.8991	0.0078	3.8997	1.9748
No log	7.0	14	3.4721	0.0078	3.4722	1.8634
No log	8.0	16	2.3668	0.0605	2.3673	1.5386
No log	9.0	18	1.7470	0.0920	1.7475	1.3219
No log	10.0	20	2.3412	0.1319	2.3417	1.5303
No log	11.0	22	2.2562	0.1706	2.2566	1.5022
No log	12.0	24	1.2881	0.0411	1.2886	1.1351
No log	13.0	26	1.0404	0.0280	1.0407	1.0202
No log	14.0	28	0.9014	0.0512	0.9017	0.9496
No log	15.0	30	1.1605	0.0910	1.1608	1.0774
No log	16.0	32	1.1896	0.1200	1.1899	1.0908
No log	17.0	34	1.0122	0.1027	1.0125	1.0063
No log	18.0	36	0.8202	0.2989	0.8204	0.9058
No log	19.0	38	0.8697	0.3558	0.8700	0.9327
No log	20.0	40	1.0159	0.3398	1.0162	1.0081
No log	21.0	42	1.3058	0.3068	1.3062	1.1429
No log	22.0	44	0.8769	0.4839	0.8771	0.9365
No log	23.0	46	0.5977	0.5495	0.5977	0.7731
No log	24.0	48	0.6799	0.5243	0.6800	0.8246
No log	25.0	50	1.0706	0.4348	1.0709	1.0349
No log	26.0	52	0.5699	0.5431	0.5698	0.7549
No log	27.0	54	0.7435	0.3911	0.7434	0.8622
No log	28.0	56	0.6940	0.4188	0.6937	0.8329
No log	29.0	58	0.6511	0.4931	0.6510	0.8069
No log	30.0	60	0.6599	0.4865	0.6598	0.8123
No log	31.0	62	0.7113	0.4739	0.7109	0.8432
No log	32.0	64	0.7996	0.4089	0.7992	0.8940
No log	33.0	66	0.6294	0.5667	0.6289	0.7930
No log	34.0	68	0.8106	0.5008	0.8103	0.9002
No log	35.0	70	0.7004	0.5545	0.7000	0.8367
No log	36.0	72	0.6410	0.5750	0.6403	0.8002
No log	37.0	74	0.6549	0.6097	0.6541	0.8088
No log	38.0	76	0.8785	0.5225	0.8778	0.9369
No log	39.0	78	0.7521	0.5733	0.7513	0.8668
No log	40.0	80	0.7732	0.5645	0.7723	0.8788
No log	41.0	82	0.7324	0.5798	0.7315	0.8553
No log	42.0	84	0.9486	0.5127	0.9480	0.9737
No log	43.0	86	0.7780	0.5712	0.7773	0.8817
No log	44.0	88	0.7449	0.5800	0.7440	0.8626
No log	45.0	90	0.6827	0.6098	0.6820	0.8258
No log	46.0	92	0.8370	0.5179	0.8365	0.9146
No log	47.0	94	0.6898	0.5888	0.6892	0.8302
No log	48.0	96	0.8110	0.5700	0.8101	0.9001
No log	49.0	98	0.7171	0.5891	0.7163	0.8463
No log	50.0	100	0.7718	0.5307	0.7712	0.8782
No log	51.0	102	0.7094	0.5810	0.7087	0.8419
No log	52.0	104	0.6957	0.5963	0.6950	0.8337
No log	53.0	106	0.7611	0.5335	0.7606	0.8722
No log	54.0	108	0.8312	0.4998	0.8308	0.9115
No log	55.0	110	0.7439	0.5584	0.7434	0.8622
No log	56.0	112	0.8599	0.5454	0.8592	0.9269
No log	57.0	114	0.9856	0.5273	0.9848	0.9923
No log	58.0	116	0.8022	0.5710	0.8014	0.8952
No log	59.0	118	0.9366	0.5001	0.9361	0.9675
No log	60.0	120	1.2114	0.4495	1.2110	1.1004
No log	61.0	122	0.9241	0.4994	0.9237	0.9611
No log	62.0	124	0.7568	0.5949	0.7562	0.8696
No log	63.0	126	0.8514	0.5493	0.8507	0.9223
No log	64.0	128	0.7083	0.6074	0.7078	0.8413
No log	65.0	130	0.7443	0.5238	0.7439	0.8625

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_changed_semanticV2_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

ASAP_changed_semanticV2_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_changed_semanticV2_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2