segformer-b0-finetuned-segments-sidewalk-2

pablojrios/segformer-b0-finetuned-segments-sidewalk-2

segformer-b0-finetuned-segments-sidewalk-2 is a machine learning model from pablojrios. 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. The card lists the license as other.

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

Downloads · 30 days

0% of all-time downloads

All-time downloads

3.1K

Public

Repo size

89.8 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin15 MB · 100%

At a glance

Library: transformers
License: other
Model type: segformer
Access: Public
Created: Aug 13, 2022
Updated: Aug 13, 2022
SHA: 4262d771

Datasets

Model card

From the Hugging Face model README

segformer-b0-finetuned-segments-sidewalk-2

This model is a fine-tuned version of nvidia/mit-b0 on the segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set:

Loss: 1.5766
Mean Iou: 0.1371
Mean Accuracy: 0.1845
Overall Accuracy: 0.7137
Per Category Iou: [nan, 0.4878460273549076, 0.7555073936058639, 0.0, 0.021023119916983492, 6.661075803708754e-07, nan, 0.0, 0.0, 0.0, 0.5945035814400078, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.5297440422960749, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.7198551864914086, 0.489491922020114, 0.7904739581298643, 0.0, 0.0, 0.0, 0.0]
Per Category Accuracy: [nan, 0.8122402393699828, 0.916307187222316, 0.0, 0.02103704204254936, 6.661204478993891e-07, nan, 0.0, 0.0, 0.0, 0.8989685161351728, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.8771164563053133, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9407576559617489, 0.6174625729307718, 0.821407178606353, 0.0, 0.0, 0.0, 0.0]

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: 6e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Per Category Iou	Per Category Accuracy
1.7378	0.5	100	1.8155	0.1247	0.1711	0.6916	[nan, 0.46555602373647126, 0.7353888954834877, 0.0, 0.009228814643632902, 0.00010122529220478676, nan, 0.0, 0.0, 0.0, 0.5739398587525921, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.5094931557231258, 0.0, 5.3423644732762526e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6692211552011066, 0.2651198767217891, 0.7633341956468725, 0.0, 0.0, 0.0, 0.0]	[nan, 0.7515868666775908, 0.9079116468110205, 0.0, 0.009233668577520995, 0.00010125030808070715, nan, 0.0, 0.0, 0.0, 0.8690972710699856, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.8791886402701642, 0.0, 5.361129513400909e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9598752209264458, 0.3079896302845186, 0.7892434570182117, 0.0, 0.0, 0.0, 0.0]
1.6547	1.0	200	1.5766	0.1371	0.1845	0.7137	[nan, 0.4878460273549076, 0.7555073936058639, 0.0, 0.021023119916983492, 6.661075803708754e-07, nan, 0.0, 0.0, 0.0, 0.5945035814400078, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.5297440422960749, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.7198551864914086, 0.489491922020114, 0.7904739581298643, 0.0, 0.0, 0.0, 0.0]	[nan, 0.8122402393699828, 0.916307187222316, 0.0, 0.02103704204254936, 6.661204478993891e-07, nan, 0.0, 0.0, 0.0, 0.8989685161351728, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.8771164563053133, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9407576559617489, 0.6174625729307718, 0.821407178606353, 0.0, 0.0, 0.0, 0.0]

Framework versions

Transformers 4.21.1
Pytorch 1.12.1
Datasets 2.4.0
Tokenizers 0.12.1

Library: transformers
Type: segformer
License: other
Created: Aug 13, 2022
Updated: Aug 13, 2022