sdss-cnn

kensvin/sdss-cnn

sdss-cnn is a machine learning model from kensvin. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

Library: transformers
Model type: cnn
Access: Public
Created: Sep 28, 2023
Updated: Sep 28, 2023
SHA: a9068077

Model card

From the Hugging Face model README

sdss-cnn

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1573
Accuracy: 0.9505

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: 0.0001
train_batch_size: 100
eval_batch_size: 100
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	80	0.4954	0.8635
No log	2.0	160	0.2788	0.9055
No log	3.0	240	0.2239	0.9085
No log	4.0	320	0.1991	0.9325
No log	5.0	400	0.1954	0.94
No log	6.0	480	0.1854	0.9445
0.3543	7.0	560	0.1891	0.9375
0.3543	8.0	640	0.1777	0.943
0.3543	9.0	720	0.1780	0.9415
0.3543	10.0	800	0.1804	0.942
0.3543	11.0	880	0.1734	0.9475
0.3543	12.0	960	0.1689	0.947
0.2022	13.0	1040	0.1698	0.9445
0.2022	14.0	1120	0.1689	0.9405
0.2022	15.0	1200	0.1650	0.9475
0.2022	16.0	1280	0.1755	0.934
0.2022	17.0	1360	0.1635	0.944
0.2022	18.0	1440	0.1711	0.942
0.1836	19.0	1520	0.1604	0.9485
0.1836	20.0	1600	0.1595	0.95
0.1836	21.0	1680	0.1613	0.9475
0.1836	22.0	1760	0.1579	0.949
0.1836	23.0	1840	0.1593	0.946
0.1836	24.0	1920	0.1579	0.945
0.167	25.0	2000	0.1584	0.9495
0.167	26.0	2080	0.1573	0.9505
0.167	27.0	2160	0.1596	0.945
0.167	28.0	2240	0.1599	0.9435
0.167	29.0	2320	0.1565	0.9485
0.167	30.0	2400	0.1582	0.946
0.167	31.0	2480	0.1563	0.95
0.1568	32.0	2560	0.1563	0.95
0.1568	33.0	2640	0.1573	0.9495
0.1568	34.0	2720	0.1564	0.9465
0.1568	35.0	2800	0.1557	0.95
0.1568	36.0	2880	0.1554	0.949
0.1568	37.0	2960	0.1562	0.948
0.1515	38.0	3040	0.1555	0.948
0.1515	39.0	3120	0.1557	0.95
0.1515	40.0	3200	0.1559	0.9485

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Library: transformers
Type: cnn
Created: Sep 28, 2023
Updated: Sep 28, 2023