BERT_AugV8_k3_task1_organization_sp060_lw030_fold1

genki10/BERT_AugV8_k3_task1_organization_sp060_lw030_fold1

BERT_AugV8_k3_task1_organization_sp060_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. --

Downloads · 30 days

32% of all-time downloads

All-time downloads

Public

Repo size

18 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin876 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 27, 2025
Updated: Apr 3, 2025
SHA: 0037b7f3

Try a prompt

Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp060_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: 1.8245
Qwk: 0.0423
Mse: 1.8228
Rmse: 1.3501

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	8.0807	0.0	8.0778	2.8422
No log	2.0	6	5.2794	0.0289	5.2774	2.2973
No log	3.0	9	3.4618	0.0	3.4598	1.8600
No log	4.0	12	2.4932	-0.0001	2.4914	1.5784
No log	5.0	15	1.6900	0.0	1.6884	1.2994
No log	6.0	18	1.4300	0.0	1.4285	1.1952
No log	7.0	21	1.4251	0.0	1.4236	1.1931
No log	8.0	24	1.4443	0.0	1.4427	1.2011
No log	9.0	27	1.6019	0.0211	1.6003	1.2650
No log	10.0	30	1.3253	0.0315	1.3238	1.1505
No log	11.0	33	1.8429	0.0532	1.8411	1.3569
No log	12.0	36	1.2953	0.0182	1.2937	1.1374
No log	13.0	39	1.2187	0.0105	1.2173	1.1033
No log	14.0	42	1.4354	0.0404	1.4340	1.1975
No log	15.0	45	1.0999	0.0177	1.0989	1.0483
No log	16.0	48	1.4081	0.0366	1.4070	1.1862
No log	17.0	51	1.1921	0.1157	1.1910	1.0914
No log	18.0	54	1.5566	0.1368	1.5552	1.2471
No log	19.0	57	1.0976	0.2387	1.0971	1.0474
No log	20.0	60	2.2654	0.0820	2.2640	1.5046
No log	21.0	63	1.1888	0.2090	1.1883	1.0901
No log	22.0	66	2.1161	0.0653	2.1142	1.4540
No log	23.0	69	1.1794	0.1462	1.1785	1.0856
No log	24.0	72	2.0292	0.0636	2.0276	1.4239
No log	25.0	75	1.2555	0.1478	1.2551	1.1203
No log	26.0	78	2.0906	0.0540	2.0892	1.4454
No log	27.0	81	1.3792	0.0636	1.3789	1.1743
No log	28.0	84	1.9639	0.0341	1.9628	1.4010
No log	29.0	87	1.1921	0.0887	1.1916	1.0916
No log	30.0	90	1.8111	0.0510	1.8101	1.3454
No log	31.0	93	1.5348	0.0786	1.5342	1.2386
No log	32.0	96	1.9511	0.0291	1.9499	1.3964
No log	33.0	99	1.4191	0.0493	1.4182	1.1909
No log	34.0	102	1.8245	0.0423	1.8228	1.3501

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 27, 2025
Updated: Apr 3, 2025