metadata

language:
  - en
tags:
  - generated_from_trainer
metrics:
  - cer
pipeline_tag: image-to-text
base_model: microsoft/trocr-base-printed
model-index:
  - name: trocr-base-printed_captcha_ocr
    results: []

trocr-base-printed_captcha_ocr

This model is a fine-tuned version of microsoft/trocr-base-printed on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1380
Cer: 0.0075

Model description

This model extracts text from image Captcha inputs.

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)/Captcha/OCR_captcha.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology. You are welcome to test and experiment with this model, but it is at your own risk/peril.

Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/alizahidraja/captcha-data

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
10.4464	1.0	107	0.5615	0.0879
10.4464	2.0	214	0.2432	0.0262
10.4464	3.0	321	0.1380	0.0075

Framework versions

Transformers 4.22.1
Pytorch 1.12.1
Datasets 2.4.0
Tokenizers 0.12.1