trocr-large-printed-e13b_tesseract_MICR_ocr

This model is a fine-tuned version of microsoft/trocr-large-printed.

It achieves the following results on the evaluation set:

• Loss: 0.2432
• CER: 0.0036

Model description

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

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: https://github.com/DoubangoTelecom/tesseractMICR/tree/master/datasets/e13b

Histogram of Label Character Lengths

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	CER
0.486	1.0	841	0.5168	0.0428
0.2187	2.0	1682	0.2432	0.0036

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.1
• Datasets 2.13.1
• Tokenizers 0.13.3