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
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