ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold2

genki10/ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold2

ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold2 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 8, 2025
Updated: Mar 8, 2025
SHA: eb749465

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Base models

Model card

From the Hugging Face model README

ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold2

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: 0.9735
Qwk: 0.3200
Mse: 0.9733
Rmse: 0.9866

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	6	5.8878	0.0080	5.8881	2.4265
No log	2.0	12	2.9245	0.0	2.9248	1.7102
No log	3.0	18	1.6194	0.0213	1.6198	1.2727
No log	4.0	24	1.7325	0.0345	1.7328	1.3164
No log	5.0	30	1.4855	0.0823	1.4857	1.2189
No log	6.0	36	1.1889	0.1651	1.1887	1.0903
No log	7.0	42	1.1280	0.1929	1.1275	1.0619
No log	8.0	48	0.9689	0.2134	0.9685	0.9841
No log	9.0	54	1.4272	0.1832	1.4264	1.1943
No log	10.0	60	1.2315	0.2411	1.2308	1.1094
No log	11.0	66	1.6767	0.1943	1.6763	1.2947
No log	12.0	72	1.3642	0.1917	1.3640	1.1679
No log	13.0	78	1.5235	0.1944	1.5231	1.2341
No log	14.0	84	2.0727	0.1451	2.0725	1.4396
No log	15.0	90	1.5991	0.2128	1.5988	1.2644
No log	16.0	96	1.6541	0.1702	1.6538	1.2860
No log	17.0	102	1.4618	0.1787	1.4617	1.2090
No log	18.0	108	0.8675	0.3440	0.8670	0.9311
No log	19.0	114	1.1022	0.2873	1.1020	1.0498
No log	20.0	120	2.1904	0.1442	2.1905	1.4800
No log	21.0	126	1.6390	0.1768	1.6390	1.2802
No log	22.0	132	0.9015	0.3012	0.9012	0.9493
No log	23.0	138	1.1640	0.2156	1.1638	1.0788
No log	24.0	144	1.4515	0.1902	1.4514	1.2047
No log	25.0	150	1.6886	0.1810	1.6884	1.2994
No log	26.0	156	0.9759	0.2685	0.9757	0.9878
No log	27.0	162	0.9699	0.3298	0.9696	0.9847
No log	28.0	168	1.1190	0.2820	1.1188	1.0577
No log	29.0	174	1.3450	0.2003	1.3449	1.1597
No log	30.0	180	1.0749	0.2609	1.0746	1.0366
No log	31.0	186	1.0030	0.2746	1.0027	1.0014
No log	32.0	192	1.0923	0.2350	1.0918	1.0449
No log	33.0	198	1.0537	0.2439	1.0535	1.0264
No log	34.0	204	1.1813	0.2531	1.1811	1.0868
No log	35.0	210	0.9487	0.3130	0.9485	0.9739
No log	36.0	216	1.0430	0.2795	1.0427	1.0211
No log	37.0	222	0.9893	0.2980	0.9891	0.9946
No log	38.0	228	0.9735	0.3200	0.9733	0.9866

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 8, 2025
Updated: Mar 8, 2025