BERT_AugV8_k3_task1_organization_sp040_lw030_fold4

genki10/BERT_AugV8_k3_task1_organization_sp040_lw030_fold4

BERT_AugV8_k3_task1_organization_sp040_lw030_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 25, 2025
Updated: Mar 27, 2025
SHA: 20b266d1

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp040_lw030_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: 1.3278
Qwk: 0.2781
Mse: 1.3278
Rmse: 1.1523

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	3	12.4501	0.0	12.4501	3.5285
No log	2.0	6	10.5212	-0.0011	10.5212	3.2436
No log	3.0	9	7.8899	0.0018	7.8899	2.8089
No log	4.0	12	5.5932	0.0245	5.5932	2.3650
No log	5.0	15	4.2761	0.0079	4.2761	2.0679
No log	6.0	18	2.9933	0.0040	2.9933	1.7301
No log	7.0	21	1.9151	0.0582	1.9151	1.3839
No log	8.0	24	1.2896	0.0330	1.2896	1.1356
No log	9.0	27	0.9381	0.0354	0.9381	0.9686
No log	10.0	30	1.0933	0.0908	1.0933	1.0456
No log	11.0	33	1.0076	0.1769	1.0076	1.0038
No log	12.0	36	0.8221	0.3782	0.8221	0.9067
No log	13.0	39	1.3998	0.2171	1.3998	1.1831
No log	14.0	42	0.8749	0.3845	0.8749	0.9354
No log	15.0	45	1.9427	0.1744	1.9427	1.3938
No log	16.0	48	1.1084	0.3490	1.1084	1.0528
No log	17.0	51	1.5967	0.2460	1.5967	1.2636
No log	18.0	54	0.9863	0.3667	0.9863	0.9931
No log	19.0	57	1.3226	0.3021	1.3226	1.1501
No log	20.0	60	1.2850	0.3137	1.2850	1.1336
No log	21.0	63	1.5967	0.2514	1.5967	1.2636
No log	22.0	66	1.2734	0.3287	1.2734	1.1284
No log	23.0	69	1.3807	0.2992	1.3807	1.1750
No log	24.0	72	1.8979	0.2218	1.8979	1.3776
No log	25.0	75	1.3192	0.3380	1.3192	1.1486
No log	26.0	78	1.2658	0.3307	1.2658	1.1251
No log	27.0	81	1.3361	0.3130	1.3361	1.1559
No log	28.0	84	2.0906	0.1749	2.0906	1.4459
No log	29.0	87	0.9134	0.4679	0.9134	0.9557
No log	30.0	90	1.6258	0.2667	1.6258	1.2751
No log	31.0	93	1.4154	0.3067	1.4154	1.1897
No log	32.0	96	1.9664	0.1969	1.9664	1.4023
No log	33.0	99	1.4439	0.2819	1.4439	1.2016
No log	34.0	102	1.7177	0.2371	1.7177	1.3106
No log	35.0	105	1.4691	0.2505	1.4691	1.2121
No log	36.0	108	1.5478	0.2312	1.5478	1.2441
No log	37.0	111	1.6269	0.2253	1.6269	1.2755
No log	38.0	114	1.4485	0.3223	1.4485	1.2036
No log	39.0	117	1.6911	0.2759	1.6911	1.3004
No log	40.0	120	1.3448	0.3254	1.3448	1.1596
No log	41.0	123	1.6683	0.2597	1.6683	1.2916
No log	42.0	126	1.3816	0.3081	1.3816	1.1754
No log	43.0	129	1.6827	0.2368	1.6827	1.2972
No log	44.0	132	1.3278	0.2781	1.3278	1.1523

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 25, 2025
Updated: Mar 27, 2025