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---
base_model:
- microsoft/trocr-base-printed
---
# anuashok/ocr-captcha-1
This model is a fine-tuned version of [microsoft/trocr-base-printed](https://huggingface.co/microsoft/trocr-base-printed) on your custom dataset.
## Training Summary
- **CER**: 0.0496031746031746
- **Hyperparameters**:
- Learning Rate: 3.4123022229050474e-05
- Batch Size: 8
- Num Epochs: 6
- Warmup Ratio: 0.057604550826554274
- Weight Decay: 0.0716137163865213
- Num Beams: 5
- Length Penalty: 0.8270021759785869
## Usage
```python
from transformers import VisionEncoderDecoderModel, TrOCRProcessor
import torch
from PIL import Image
# Load model and processor
processor = TrOCRProcessor.from_pretrained("anuashok/ocr-captcha-1")
model = VisionEncoderDecoderModel.from_pretrained("anuashok/ocr-captcha-1")
# Load image
image = Image.open('path_to_your_image.jpg').convert("RGB")
# Prepare image
pixel_values = processor(image, return_tensors="pt").pixel_values
# Generate text
generated_ids = model.generate(pixel_values)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(generated_text) |