Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold2

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold2

Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_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 11, 2025
Updated: Mar 11, 2025
SHA: 484b4f8b

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Base models

Model card

From the Hugging Face model README

Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_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: 0.5687
Qwk: 0.6375
Mse: 0.5687
Rmse: 0.7541

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	4	8.1808	0.0	8.1808	2.8602
No log	2.0	8	4.7888	0.0	4.7888	2.1883
No log	3.0	12	3.2361	0.0	3.2361	1.7989
No log	4.0	16	2.0343	0.0246	2.0343	1.4263
No log	5.0	20	1.3655	0.0	1.3655	1.1685
No log	6.0	24	1.1253	0.0837	1.1253	1.0608
No log	7.0	28	1.0562	0.0348	1.0562	1.0277
No log	8.0	32	1.2766	0.0348	1.2766	1.1299
No log	9.0	36	0.8819	0.4596	0.8819	0.9391
No log	10.0	40	0.6288	0.5947	0.6288	0.7930
No log	11.0	44	0.6164	0.6075	0.6164	0.7851
No log	12.0	48	0.8241	0.6	0.8241	0.9078
No log	13.0	52	0.6493	0.6715	0.6493	0.8058
No log	14.0	56	0.9239	0.6230	0.9239	0.9612
No log	15.0	60	0.6748	0.6364	0.6748	0.8215
No log	16.0	64	0.6578	0.6827	0.6578	0.8110
No log	17.0	68	0.6887	0.6562	0.6887	0.8299
No log	18.0	72	0.6061	0.6723	0.6061	0.7785
No log	19.0	76	0.8742	0.6156	0.8742	0.9350
No log	20.0	80	0.5913	0.7110	0.5913	0.7690
No log	21.0	84	0.6574	0.6410	0.6574	0.8108
No log	22.0	88	0.5795	0.6770	0.5795	0.7613
No log	23.0	92	0.5896	0.6471	0.5896	0.7678
No log	24.0	96	0.8382	0.6386	0.8382	0.9155
No log	25.0	100	0.6332	0.6615	0.6332	0.7957
No log	26.0	104	0.6459	0.6373	0.6459	0.8037
No log	27.0	108	0.7128	0.6503	0.7128	0.8443
No log	28.0	112	0.6368	0.6637	0.6368	0.7980
No log	29.0	116	0.6640	0.6764	0.6640	0.8149
No log	30.0	120	0.9352	0.6303	0.9352	0.9671
No log	31.0	124	0.6209	0.6384	0.6209	0.7880
No log	32.0	128	0.7021	0.6585	0.7021	0.8379
No log	33.0	132	0.6372	0.6540	0.6372	0.7982
No log	34.0	136	0.7244	0.6615	0.7244	0.8511
No log	35.0	140	0.5659	0.6512	0.5659	0.7522
No log	36.0	144	0.8521	0.6126	0.8521	0.9231
No log	37.0	148	0.5744	0.6416	0.5744	0.7579
No log	38.0	152	0.7699	0.6608	0.7699	0.8774
No log	39.0	156	0.7409	0.6508	0.7409	0.8607
No log	40.0	160	0.5687	0.6375	0.5687	0.7541

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 11, 2025
Updated: Mar 11, 2025