dog-food-fine / README.md
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---
tags:
- autotrain
- vision
- image-classification
datasets:
- lewtun/dog_food
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
example_title: Palace
library_name: transformers
co2_eq_emissions:
emissions: 6.799888815236616
eval_info:
col_mapping: test
model-index:
- name: NimaBoscarino/dog_food
results:
- task:
type: image-classification
name: Image Classification
dataset:
name: lewtun/dog_food
type: lewtun/dog_food
config: lewtun--dog_food
split: test
metrics:
- name: Accuracy
type: accuracy
value: 1.0
verified: true
- name: Precision Macro
type: precision
value: 1.0
verified: true
- name: Precision Micro
type: precision
value: 1.0
verified: true
- name: Precision Weighted
type: precision
value: 1.0
verified: true
- name: Recall Macro
type: recall
value: 1.0
verified: true
- name: Recall Micro
type: recall
value: 1.0
verified: true
- name: Recall Weighted
type: recall
value: 1.0
verified: true
- name: F1 Macro
type: f1
value: 1.0
verified: true
- name: F1 Micro
type: f1
value: 1.0
verified: true
- name: F1 Weighted
type: f1
value: 1.0
verified: true
- name: loss
type: loss
value: 1.848173087637406e-05
verified: true
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1647758504
- CO2 Emissions (in grams): 6.7999
## Validation Metrics
- Loss: 0.001
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000