---
tags:
- autotrain
- vision
- image-classification
- lam
datasets:
- Livingwithmachines/MapReader_Data_SIGSPATIAL_2022
widget:
- src: >-
    https://huggingface.co/davanstrien/autotrain-mapreader-5000-40830105612/resolve/main/1.png
  example_title: patch
- src: >-
    https://huggingface.co/davanstrien/autotrain-mapreader-5000-40830105612/resolve/main/271.png
  example_title: patch
co2_eq_emissions:
  emissions: 0.008077657735064319
pipeline_tag: image-classification
---

# Model Trained Using AutoTrain

Image classification model trained to predict whether a patch of a historic map contains 'railspace' or not. See the [dataset](https://huggingface.co/datasets/Livingwithmachines/MapReader_Data_SIGSPATIAL_2022) used for training for more information on the labels.

- Problem type: Multi-class Classification
- Model ID: 40830105612
- CO2 Emissions (in grams): 0.0081

## Validation Metrics

- Loss: 0.038
- Accuracy: 0.995
- Macro F1: 0.983
- Micro F1: 0.995
- Weighted F1: 0.995
- Macro Precision: 0.991
- Micro Precision: 0.995
- Weighted Precision: 0.995
- Macro Recall: 0.975
- Micro Recall: 0.995
- Weighted Recall: 0.995