| 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 |