BERT_AugV8_k3_task1_organization_sp040_lw030_fold1

genki10/BERT_AugV8_k3_task1_organization_sp040_lw030_fold1

BERT_AugV8_k3_task1_organization_sp040_lw030_fold1 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: 47e9b37d

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp040_lw030_fold1

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: 1.3434
Qwk: 0.2906
Mse: 1.3422
Rmse: 1.1585

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	10.3147	0.0037	10.3121	3.2113
No log	2.0	6	9.1580	0.0	9.1555	3.0258
No log	3.0	9	7.3035	0.0	7.3012	2.7021
No log	4.0	12	6.3869	0.0	6.3846	2.5268
No log	5.0	15	4.9498	0.0	4.9477	2.2243
No log	6.0	18	3.4721	0.0	3.4702	1.8628
No log	7.0	21	2.5844	0.0	2.5826	1.6071
No log	8.0	24	1.8393	0.0545	1.8377	1.3556
No log	9.0	27	1.4445	0.0106	1.4430	1.2013
No log	10.0	30	1.2078	0.0379	1.2063	1.0983
No log	11.0	33	1.3604	0.1105	1.3589	1.1657
No log	12.0	36	1.0079	0.1027	1.0066	1.0033
No log	13.0	39	2.0691	0.1855	2.0674	1.4379
No log	14.0	42	0.9635	0.2310	0.9622	0.9809
No log	15.0	45	1.6380	0.1583	1.6364	1.2792
No log	16.0	48	1.4392	0.1889	1.4379	1.1991
No log	17.0	51	1.4403	0.2113	1.4393	1.1997
No log	18.0	54	1.3118	0.2336	1.3107	1.1449
No log	19.0	57	1.2430	0.2636	1.2421	1.1145
No log	20.0	60	1.6902	0.2224	1.6892	1.2997
No log	21.0	63	0.9661	0.4332	0.9656	0.9827
No log	22.0	66	3.2824	0.1059	3.2812	1.8114
No log	23.0	69	1.4876	0.2997	1.4871	1.2194
No log	24.0	72	1.2995	0.3171	1.2988	1.1396
No log	25.0	75	1.8312	0.2203	1.8301	1.3528
No log	26.0	78	1.3391	0.3111	1.3381	1.1567
No log	27.0	81	2.2718	0.1607	2.2704	1.5068
No log	28.0	84	1.4532	0.2718	1.4520	1.2050
No log	29.0	87	1.7063	0.2326	1.7047	1.3056
No log	30.0	90	1.7264	0.2287	1.7247	1.3133
No log	31.0	93	1.5299	0.2686	1.5285	1.2363
No log	32.0	96	1.9078	0.1838	1.9062	1.3807
No log	33.0	99	1.5124	0.2585	1.5109	1.2292
No log	34.0	102	1.6630	0.2345	1.6616	1.2890
No log	35.0	105	2.3536	0.1623	2.3519	1.5336
No log	36.0	108	1.3434	0.2906	1.3422	1.1585

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