Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold4

genki10/Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold4

Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold4 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 1, 2025
Updated: Mar 1, 2025
SHA: 83f0399c

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV8_k1_task1_organization_k1_k1_fold4

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: 1.0540
Qwk: 0.3882
Mse: 1.0540
Rmse: 1.0267

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	11.2547	-0.0278	11.2547	3.3548
No log	2.0	4	9.2793	0.0018	9.2793	3.0462
No log	3.0	6	7.6917	0.0018	7.6917	2.7734
No log	4.0	8	6.3047	0.0	6.3047	2.5109
No log	5.0	10	5.2925	0.0209	5.2925	2.3006
No log	6.0	12	4.3891	0.0079	4.3891	2.0950
No log	7.0	14	3.5396	0.0040	3.5396	1.8814
No log	8.0	16	2.8185	0.0040	2.8185	1.6789
No log	9.0	18	2.2812	0.1837	2.2812	1.5104
No log	10.0	20	1.7964	0.0420	1.7964	1.3403
No log	11.0	22	1.4350	0.0420	1.4350	1.1979
No log	12.0	24	1.1900	0.0420	1.1900	1.0909
No log	13.0	26	1.0902	0.0420	1.0902	1.0441
No log	14.0	28	0.9996	0.0710	0.9996	0.9998
No log	15.0	30	0.8047	0.3332	0.8047	0.8970
No log	16.0	32	0.8676	0.3203	0.8676	0.9314
No log	17.0	34	1.2045	0.2408	1.2045	1.0975
No log	18.0	36	0.9140	0.3870	0.9140	0.9560
No log	19.0	38	0.9522	0.3965	0.9522	0.9758
No log	20.0	40	1.0493	0.4224	1.0493	1.0243
No log	21.0	42	0.9983	0.4003	0.9983	0.9992
No log	22.0	44	1.1480	0.3405	1.1480	1.0714
No log	23.0	46	1.4590	0.2501	1.4590	1.2079
No log	24.0	48	1.2248	0.2842	1.2248	1.1067
No log	25.0	50	1.2078	0.3562	1.2078	1.0990
No log	26.0	52	1.0767	0.3390	1.0767	1.0376
No log	27.0	54	1.0989	0.3286	1.0989	1.0483
No log	28.0	56	1.1128	0.3081	1.1128	1.0549
No log	29.0	58	1.1738	0.2482	1.1738	1.0834
No log	30.0	60	1.1636	0.1953	1.1636	1.0787
No log	31.0	62	1.1334	0.2570	1.1334	1.0646
No log	32.0	64	1.2167	0.2444	1.2167	1.1030
No log	33.0	66	1.1756	0.2893	1.1756	1.0842
No log	34.0	68	1.0459	0.4039	1.0459	1.0227
No log	35.0	70	1.0374	0.3820	1.0374	1.0185
No log	36.0	72	1.0969	0.3622	1.0969	1.0473
No log	37.0	74	1.1132	0.3563	1.1132	1.0551
No log	38.0	76	1.0956	0.3373	1.0956	1.0467
No log	39.0	78	1.0638	0.3631	1.0638	1.0314
No log	40.0	80	1.0540	0.3882	1.0540	1.0267

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 1, 2025
Updated: Mar 1, 2025