bert-petco-text_content-ctr

yimiwang/bert-petco-text_content-ctr

bert-petco-text_content-ctr is a text classification model from yimiwang. 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

7% of all-time downloads

All-time downloads

241

Public

Parameters

109M

43 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors876 MB · 61%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Apr 16, 2024
Updated: Apr 17, 2024
SHA: 230e7084

Try a prompt

Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

bert-petco-text_content-ctr

This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0034
Mse: 0.0034
Rmse: 0.0586
Mae: 0.0408
R2: 0.4036
Accuracy: 0.6833

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Rmse	Mae	R2	Accuracy
0.0239	1.0	15	0.0049	0.0049	0.0701	0.0519	0.1473	0.5833
0.0095	2.0	30	0.0047	0.0047	0.0688	0.0537	0.1774	0.5667
0.0071	3.0	45	0.0057	0.0057	0.0756	0.0643	0.0065	0.4
0.0062	4.0	60	0.0046	0.0046	0.0675	0.0544	0.2089	0.5
0.0058	5.0	75	0.0048	0.0048	0.0692	0.0495	0.1682	0.6833
0.0048	6.0	90	0.0046	0.0046	0.0678	0.0543	0.2014	0.5
0.0042	7.0	105	0.0039	0.0039	0.0621	0.0465	0.3295	0.6833
0.0034	8.0	120	0.0038	0.0038	0.0617	0.0444	0.3382	0.6667
0.0031	9.0	135	0.0040	0.0040	0.0630	0.0462	0.3106	0.6667
0.0037	10.0	150	0.0040	0.0040	0.0629	0.0439	0.3140	0.7167
0.0028	11.0	165	0.0041	0.0041	0.0638	0.0439	0.2942	0.6833
0.0027	12.0	180	0.0041	0.0041	0.0642	0.0447	0.2854	0.7167
0.0026	13.0	195	0.0036	0.0036	0.0598	0.0422	0.3788	0.7
0.0025	14.0	210	0.0034	0.0034	0.0587	0.0420	0.4021	0.6833
0.002	15.0	225	0.0034	0.0034	0.0586	0.0408	0.4036	0.6833
0.0022	16.0	240	0.0037	0.0037	0.0607	0.0420	0.3610	0.7
0.0019	17.0	255	0.0037	0.0037	0.0607	0.0416	0.3595	0.7167
0.0018	18.0	270	0.0037	0.0037	0.0612	0.0423	0.3493	0.6833
0.0018	19.0	285	0.0036	0.0036	0.0597	0.0409	0.3804	0.7167
0.0019	20.0	300	0.0035	0.0035	0.0589	0.0407	0.3967	0.6667

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 16, 2024
Updated: Apr 17, 2024