Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold0

genki10/Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold0

Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold0 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 9, 2025
Updated: Mar 9, 2025
SHA: 48ca1570

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Base models

Model card

From the Hugging Face model README

Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold0

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6668
Qwk: 0.6054
Mse: 0.6668
Rmse: 0.8166

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

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	9.0716	0.0	9.0716	3.0119
No log	2.0	4	7.6769	0.0	7.6769	2.7707
No log	3.0	6	6.9098	0.0	6.9098	2.6286
No log	4.0	8	6.0644	0.0210	6.0644	2.4626
No log	5.0	10	5.2912	0.0115	5.2912	2.3003
No log	6.0	12	4.5062	0.0039	4.5062	2.1228
No log	7.0	14	3.7864	0.0	3.7864	1.9459
No log	8.0	16	3.0479	0.0	3.0479	1.7458
No log	9.0	18	2.4075	0.0861	2.4075	1.5516
No log	10.0	20	1.8354	0.0316	1.8354	1.3548
No log	11.0	22	1.4413	0.0316	1.4413	1.2005
No log	12.0	24	1.1582	0.0106	1.1582	1.0762
No log	13.0	26	0.9439	0.0106	0.9439	0.9716
No log	14.0	28	0.8062	0.2701	0.8062	0.8979
No log	15.0	30	0.7511	0.1774	0.7511	0.8667
No log	16.0	32	0.7066	0.2035	0.7066	0.8406
No log	17.0	34	0.7389	0.1502	0.7389	0.8596
No log	18.0	36	0.7109	0.1948	0.7109	0.8431
No log	19.0	38	0.7572	0.2164	0.7572	0.8702
No log	20.0	40	0.6392	0.3467	0.6392	0.7995
No log	21.0	42	0.9269	0.3837	0.9269	0.9628
No log	22.0	44	0.5373	0.5472	0.5373	0.7330
No log	23.0	46	0.6021	0.5434	0.6021	0.7759
No log	24.0	48	0.5279	0.6018	0.5279	0.7265
No log	25.0	50	0.4793	0.6293	0.4793	0.6923
No log	26.0	52	0.6096	0.5941	0.6096	0.7808
No log	27.0	54	0.4904	0.6587	0.4904	0.7003
No log	28.0	56	0.8171	0.5927	0.8171	0.9040
No log	29.0	58	0.5992	0.6634	0.5992	0.7741
No log	30.0	60	0.5510	0.6545	0.5510	0.7423
No log	31.0	62	0.5527	0.6637	0.5527	0.7434
No log	32.0	64	0.6269	0.6195	0.6269	0.7918
No log	33.0	66	0.4601	0.6423	0.4601	0.6783
No log	34.0	68	0.4864	0.6513	0.4864	0.6974
No log	35.0	70	0.5753	0.6277	0.5753	0.7585
No log	36.0	72	0.5076	0.6685	0.5076	0.7125
No log	37.0	74	0.4978	0.6588	0.4978	0.7055
No log	38.0	76	0.6522	0.6001	0.6522	0.8076
No log	39.0	78	0.4717	0.6096	0.4717	0.6868
No log	40.0	80	0.5010	0.6298	0.5010	0.7078
No log	41.0	82	0.7791	0.5956	0.7791	0.8826
No log	42.0	84	0.5596	0.6450	0.5596	0.7481
No log	43.0	86	0.6138	0.6101	0.6138	0.7834
No log	44.0	88	0.5406	0.6364	0.5406	0.7352
No log	45.0	90	0.6799	0.6102	0.6799	0.8246
No log	46.0	92	0.7963	0.5820	0.7963	0.8924
No log	47.0	94	0.5012	0.6453	0.5012	0.7079
No log	48.0	96	0.4821	0.6527	0.4821	0.6943
No log	49.0	98	0.5172	0.6596	0.5172	0.7192
No log	50.0	100	0.5050	0.6628	0.5050	0.7106
No log	51.0	102	0.6886	0.6056	0.6886	0.8298
No log	52.0	104	0.7618	0.5921	0.7618	0.8728
No log	53.0	106	0.5282	0.6434	0.5282	0.7268
No log	54.0	108	0.4792	0.6555	0.4792	0.6922
No log	55.0	110	0.4883	0.6647	0.4883	0.6988
No log	56.0	112	0.6668	0.6054	0.6668	0.8166

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 9, 2025
Updated: Mar 9, 2025