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README.md
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model-index:
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- name: trocr-large-printed-cmc7_tesseract_MICR_ocr
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# trocr-large-printed-cmc7_tesseract_MICR_ocr
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This model is a fine-tuned version of [microsoft/trocr-large-printed](https://huggingface.co/microsoft/trocr-large-printed)
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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### Training results
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The Character Error Rate (CER) for this model is 0.004970720413999727
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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model-index:
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- name: trocr-large-printed-cmc7_tesseract_MICR_ocr
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results: []
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license: bsd-3-clause
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language:
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- en
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metrics:
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- cer
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pipeline_tag: image-to-text
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---
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# trocr-large-printed-cmc7_tesseract_MICR_ocr
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This model is a fine-tuned version of [microsoft/trocr-large-printed](https://huggingface.co/microsoft/trocr-large-printed).
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## Model description
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For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Optical%20Character%20Recognition%20(OCR)/Tesseract%20MICR%20(CMC7%20Dataset)/TrOCR_cmc7_tesseractMICR.ipynb
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## Intended uses & limitations
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This model is intended to demonstrate my ability to solve a complex problem using technology.
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## Training and evaluation data
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Dataset Source: https://github.com/DoubangoTelecom/tesseractMICR/tree/master/datasets/cmc7
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**Histogram of Label Character Lengths**
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/Tesseract%20MICR%20(CMC7%20Dataset)/Images/Histogram%20of%20Label%20Character%20Length.png)
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## Training procedure
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### Training results
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The Character Error Rate (CER) for this model is 0.004970720413999727.
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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