# finetuned-MS-swin-doc-text-classifer

This model is a fine-tuned version of Microsoft’s Swin Transformer tiny-sized model [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the ernie-ai/image-text-examples-ar-cn-latin-notext dataset.
It achieves the following results on the evaluation set:
- Loss: 0.267
- Accuracy: 0.882

## Model description

It is an image classificatin model fine-tuned to predict whether an images contains text and if that text is Latin script, Chinese or Arabic. It also classifies non-text images.

## Training and evaluation data

Dataset: [ernie-ai/image-text-examples-ar-cn-latin-notext]

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3338392240
- CO2 Emissions (in grams): 2.2267

## Validation Metrics

- Loss: 0.267
- Accuracy: 0.882
- Macro F1: 0.862
- Micro F1: 0.882
- Weighted F1: 0.880
- Macro Precision: 0.877
- Micro Precision: 0.882
- Weighted Precision: 0.883
- Macro Recall: 0.856
- Micro Recall: 0.882
- Weighted Recall: 0.882
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["ernie-ai/autotrain-data-document-text-language-ar-en-zh"], "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": 2.2266908460523576}}
transformers pytorch swin image-classification autotrain vision dataset:ernie-ai/autotrain-data-document-text-language-ar-en-zh co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-ernie-ai/autotrain-data-document-text-language-ar-en-zh #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 

# finetuned-MS-swin-doc-text-classifer

This model is a fine-tuned version of Microsoft’s Swin Transformer tiny-sized model microsoft/swin-tiny-patch4-window7-224 on the ernie-ai/image-text-examples-ar-cn-latin-notext dataset.
It achieves the following results on the evaluation set:
- Loss: 0.267
- Accuracy: 0.882

## Model description

It is an image classificatin model fine-tuned to predict whether an images contains text and if that text is Latin script, Chinese or Arabic. It also classifies non-text images.

## Training and evaluation data

Dataset: [ernie-ai/image-text-examples-ar-cn-latin-notext]

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3338392240
- CO2 Emissions (in grams): 2.2267

## Validation Metrics

- Loss: 0.267
- Accuracy: 0.882
- Macro F1: 0.862
- Micro F1: 0.882
- Weighted F1: 0.880
- Macro Precision: 0.877
- Micro Precision: 0.882
- Weighted Precision: 0.883
- Macro Recall: 0.856
- Micro Recall: 0.882
- Weighted Recall: 0.882
# finetuned-MS-swin-doc-text-classifer

This model is a fine-tuned version of Microsoft’s Swin Transformer tiny-sized model microsoft/swin-tiny-patch4-window7-224 on the ernie-ai/image-text-examples-ar-cn-latin-notext dataset.
It achieves the following results on the evaluation set:
- Loss: 0.267
- Accuracy: 0.882 ## Model description

It is an image classificatin model fine-tuned to predict whether an images contains text and if that text is Latin script, Chinese or Arabic. It also classifies non-text images. ## Training and evaluation data

Dataset: [ernie-ai/image-text-examples-ar-cn-latin-notext] # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3338392240
- CO2 Emissions (in grams): 2.2267 ## Validation Metrics

- Loss: 0.267
- Accuracy: 0.882
- Macro F1: 0.862
- Micro F1: 0.882
- Weighted F1: 0.880
- Macro Precision: 0.877
- Micro Precision: 0.882
- Weighted Precision: 0.883
- Macro Recall: 0.856
- Micro Recall: 0.882
- Weighted Recall: 0.882
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-ernie-ai/autotrain-data-document-text-language-ar-en-zh #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # finetuned-MS-swin-doc-text-classifer

This model is a fine-tuned version of Microsoft’s Swin Transformer tiny-sized model microsoft/swin-tiny-patch4-window7-224 on the ernie-ai/image-text-examples-ar-cn-latin-notext dataset.
It achieves the following results on the evaluation set:
- Loss: 0.267
- Accuracy: 0.882 ## Model description

It is an image classificatin model fine-tuned to predict whether an images contains text and if that text is Latin script, Chinese or Arabic. It also classifies non-text images. ## Training and evaluation data

Dataset: [ernie-ai/image-text-examples-ar-cn-latin-notext] # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3338392240
- CO2 Emissions (in grams): 2.2267 ## Validation Metrics

- Loss: 0.267
- Accuracy: 0.882
- Macro F1: 0.862
- Micro F1: 0.882
- Weighted F1: 0.880
- Macro Precision: 0.877
- Micro Precision: 0.882
- Weighted Precision: 0.883
- Macro Recall: 0.856
- Micro Recall: 0.882
- Weighted Recall: 0.882
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-ernie-ai/autotrain-data-document-text-language-ar-en-zh #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# finetuned-MS-swin-doc-text-classifer

This model is a fine-tuned version of Microsoft’s Swin Transformer tiny-sized model microsoft/swin-tiny-patch4-window7-224 on the ernie-ai/image-text-examples-ar-cn-latin-notext dataset.
It achieves the following results on the evaluation set:
- Loss: 0.267
- Accuracy: 0.882## Model description

It is an image classificatin model fine-tuned to predict whether an images contains text and if that text is Latin script, Chinese or Arabic. It also classifies non-text images.## Training and evaluation data

Dataset: [ernie-ai/image-text-examples-ar-cn-latin-notext]# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3338392240
- CO2 Emissions (in grams): 2.2267## Validation Metrics

- Loss: 0.267
- Accuracy: 0.882
- Macro F1: 0.862
- Micro F1: 0.882
- Weighted F1: 0.880
- Macro Precision: 0.877
- Micro Precision: 0.882
- Weighted Precision: 0.883
- Macro Recall: 0.856
- Micro Recall: 0.882
- Weighted Recall: 0.882