
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 55447129537
- CO2 Emissions (in grams): 1.6025

## Validation Metrics

- Loss: 0.958
- Accuracy: 0.615
- Macro F1: 0.615
- Micro F1: 0.615
- Weighted F1: 0.615
- Macro Precision: 0.618
- Micro Precision: 0.615
- Weighted Precision: 0.618
- Macro Recall: 0.615
- Micro Recall: 0.615
- Weighted Recall: 0.615
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["biglam/dating-historical-color-images"], "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"}], "co2_eq_emissions": {"emissions": 1.602513246354456}}
transformers pytorch safetensors swin image-classification autotrain vision dataset:biglam/dating-historical-color-images co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #swin #image-classification #autotrain #vision #dataset-biglam/dating-historical-color-images #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 55447129537
- CO2 Emissions (in grams): 1.6025

## Validation Metrics

- Loss: 0.958
- Accuracy: 0.615
- Macro F1: 0.615
- Micro F1: 0.615
- Weighted F1: 0.615
- Macro Precision: 0.618
- Micro Precision: 0.615
- Weighted Precision: 0.618
- Macro Recall: 0.615
- Micro Recall: 0.615
- Weighted Recall: 0.615
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 55447129537
- CO2 Emissions (in grams): 1.6025 ## Validation Metrics

- Loss: 0.958
- Accuracy: 0.615
- Macro F1: 0.615
- Micro F1: 0.615
- Weighted F1: 0.615
- Macro Precision: 0.618
- Micro Precision: 0.615
- Weighted Precision: 0.618
- Macro Recall: 0.615
- Micro Recall: 0.615
- Weighted Recall: 0.615
TAGS
#transformers #pytorch #safetensors #swin #image-classification #autotrain #vision #dataset-biglam/dating-historical-color-images #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 55447129537
- CO2 Emissions (in grams): 1.6025 ## Validation Metrics

- Loss: 0.958
- Accuracy: 0.615
- Macro F1: 0.615
- Micro F1: 0.615
- Weighted F1: 0.615
- Macro Precision: 0.618
- Micro Precision: 0.615
- Weighted Precision: 0.618
- Macro Recall: 0.615
- Micro Recall: 0.615
- Weighted Recall: 0.615