convnext-tiny-224-finetuned-brs

sergiocannata/convnext-tiny-224-finetuned-brs

convnext-tiny-224-finetuned-brs is a image classification model from sergiocannata. 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. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: convnext
Access: Public
Created: Oct 29, 2022
Updated: Oct 29, 2022
SHA: d9e3c729

Datasets

imagefolder

Model card

From the Hugging Face model README

convnext-tiny-224-finetuned-brs

This model is a fine-tuned version of facebook/convnext-tiny-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.8667
Accuracy: 0.8235
F1: 0.7273
Precision (ppv): 0.8
Recall (sensitivity): 0.6667
Specificity: 0.9091
Npv: 0.8333
Auc: 0.7879

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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision (ppv)	Recall (sensitivity)	Specificity	Npv	Auc
0.6766	6.25	100	0.7002	0.4706	0.5263	0.3846	0.8333	0.2727	0.75	0.5530
0.6408	12.49	200	0.6770	0.6471	0.5714	0.5	0.6667	0.6364	0.7778	0.6515
0.464	18.74	300	0.6624	0.5882	0.5882	0.4545	0.8333	0.4545	0.8333	0.6439
0.4295	24.98	400	0.6938	0.5294	0.5	0.4	0.6667	0.4545	0.7143	0.5606
0.3952	31.25	500	0.5974	0.7059	0.6154	0.5714	0.6667	0.7273	0.8	0.6970
0.1082	37.49	600	0.6163	0.6471	0.5	0.5	0.5	0.7273	0.7273	0.6136
0.1997	43.74	700	0.6155	0.7059	0.6154	0.5714	0.6667	0.7273	0.8	0.6970
0.1267	49.98	800	0.9063	0.6471	0.5714	0.5	0.6667	0.6364	0.7778	0.6515
0.1178	56.25	900	0.8672	0.7059	0.6667	0.5556	0.8333	0.6364	0.875	0.7348
0.2008	62.49	1000	0.7049	0.8235	0.7692	0.7143	0.8333	0.8182	0.9	0.8258
0.0996	68.74	1100	0.4510	0.8235	0.7692	0.7143	0.8333	0.8182	0.9	0.8258
0.0115	74.98	1200	0.7561	0.8235	0.7692	0.7143	0.8333	0.8182	0.9	0.8258
0.0177	81.25	1300	1.0400	0.7059	0.6667	0.5556	0.8333	0.6364	0.875	0.7348
0.0261	87.49	1400	0.9139	0.8235	0.7692	0.7143	0.8333	0.8182	0.9	0.8258
0.028	93.74	1500	0.7367	0.7647	0.7143	0.625	0.8333	0.7273	0.8889	0.7803
0.0056	99.98	1600	0.8667	0.8235	0.7273	0.8	0.6667	0.9091	0.8333	0.7879

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1

Task: Image Classification
Library: transformers
Type: convnext
License: apache-2.0
Created: Oct 29, 2022
Updated: Oct 29, 2022