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
License Notice
This model is a fine-tuned derivative of a pretrained model. Users must comply with the original model license.
Dataset Notice
This model was fine-tuned on third-party datasets which may have separate licenses or usage restrictions.