resnet-50-finetuned-barkley

alyzbane/resnet-50-finetuned-barkley

resnet-50-finetuned-barkley is a image classification model from alyzbane. Use it when you need a label for an image. 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

1% of all-time downloads

All-time downloads

537

Public

Parameters

23.6M

96.1 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors94.3 MB · 97%

At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: resnet
Access: Public
Created: Oct 17, 2024
Updated: Oct 18, 2024
SHA: d266b3bd

Base models

microsoft/resnet-50

Model card

From the Hugging Face model README

resnet-50-finetuned-barkley

This model is a fine-tuned version of microsoft/resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9221
Precision: 0.8780
Recall: 0.8618
F1: 0.8574
Accuracy: 0.8744
Top1 Accuracy: 0.8618
Error Rate: 0.1256

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: 0.0002
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Top1 Accuracy	Error Rate
1.6171	1.0	38	1.6195	0.0663	0.1513	0.0664	0.1738	0.1513	0.8262
1.6149	2.0	76	1.6160	0.2953	0.1579	0.0802	0.1785	0.1579	0.8215
1.6119	3.0	114	1.6112	0.0804	0.1579	0.0834	0.1772	0.1579	0.8228
1.6041	4.0	152	1.6015	0.4161	0.1974	0.1461	0.2155	0.1974	0.7845
1.5945	5.0	190	1.5895	0.4089	0.2895	0.2428	0.3092	0.2895	0.6908
1.5777	6.0	228	1.5710	0.5764	0.4408	0.3944	0.4663	0.4408	0.5337
1.561	7.0	266	1.5490	0.6013	0.4934	0.4516	0.5173	0.5	0.4827
1.536	8.0	304	1.5222	0.6377	0.5132	0.4711	0.5450	0.5132	0.4550
1.5081	9.0	342	1.4912	0.7595	0.5987	0.5869	0.6250	0.5987	0.3750
1.4756	10.0	380	1.4566	0.7579	0.6447	0.6293	0.6683	0.6447	0.3317
1.4387	11.0	418	1.4156	0.7914	0.6776	0.6692	0.6985	0.6776	0.3015
1.3993	12.0	456	1.3737	0.7997	0.6842	0.6732	0.7080	0.6842	0.2920
1.358	13.0	494	1.3288	0.8290	0.7039	0.7048	0.7232	0.7039	0.2768
1.3139	14.0	532	1.2806	0.8277	0.7434	0.7373	0.7592	0.75	0.2408
1.262	15.0	570	1.2345	0.8478	0.7697	0.7664	0.7829	0.7697	0.2171
1.2184	16.0	608	1.1887	0.8323	0.7697	0.7654	0.7818	0.7697	0.2182
1.1803	17.0	646	1.1408	0.8423	0.7763	0.7735	0.7931	0.7763	0.2069
1.1422	18.0	684	1.0966	0.8594	0.8158	0.8100	0.8317	0.8158	0.1683
1.1032	19.0	722	1.0587	0.8431	0.8026	0.7969	0.8145	0.8026	0.1855
1.058	20.0	760	1.0289	0.8610	0.8355	0.8301	0.8487	0.8355	0.1513
1.0252	21.0	798	0.9918	0.8576	0.8421	0.8370	0.8534	0.8421	0.1466
1.002	22.0	836	0.9727	0.8677	0.8487	0.8435	0.8611	0.8487	0.1389
0.9812	23.0	874	0.9465	0.8795	0.8553	0.8497	0.8678	0.8553	0.1322
0.9636	24.0	912	0.9331	0.8820	0.8553	0.8485	0.8699	0.8553	0.1301
0.9591	25.0	950	0.9221	0.8780	0.8618	0.8574	0.8744	0.8618	0.1256
0.948	26.0	988	0.9158	0.8780	0.8618	0.8574	0.8744	0.8684	0.1256
0.9384	27.0	1026	0.9017	0.8685	0.8487	0.8431	0.8601	0.8487	0.1399

Framework versions

Transformers 4.45.2
Pytorch 2.5.0+cu121
Datasets 3.0.1
Tokenizers 0.20.1

Task: Image Classification
Library: transformers
Type: resnet
License: apache-2.0
Created: Oct 17, 2024
Updated: Oct 18, 2024