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--- |
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tags: |
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- generated_from_trainer |
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- TrOCR |
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model-index: |
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- name: trocr-large-printed-e13b_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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--- |
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# trocr-large-printed-e13b_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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It achieves the following results on the evaluation set: |
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- Loss: 0.2432 |
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- CER: 0.0036 |
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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(E15B%20Dataset)/TrOCR-e13b%20-%20tesseractMICR.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/e13b |
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__Histogram of Label Character Lengths__ |
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/Tesseract%20MICR%20(E15B%20Dataset)/Images/Histogram%20of%20Label%20Character%20Length.png) |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | CER | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.486 | 1.0 | 841 | 0.5168 | 0.0428 | |
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| 0.2187 | 2.0 | 1682 | 0.2432 | 0.0036 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
