Update README.md

README.md

@@ -1,3 +1,65 @@
 ---
 license: apache-2.0
+language:
+- ko
+metrics:
+- cer
+- wer
+pipeline_tag: image-to-text
 ---
+
+# trOCR-youtube-kor-OCR
+
+fine-tuned for VisionEncoderDecoderModel(encoder , decoder)
+encoder = 'facebook/deit-base-distilled-patch16-384'
+decoder = 'klue/roberta-base'
+
+## How to Get Started with the Model
+
+```python
+from transformers import VisionEncoderDecoderModel,AutoTokenizer, TrOCRProcessor
+import torch
+from PIL import Image
+
+
+device = torch.device('cuda') # change 'cuda' if you need.
+
+image_path='(your image path)'
+image = Image.open(image_path)
+#model can be .jpg or .png
+#hugging face download: https://huggingface.co/gg4ever/trOCR-final
+
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
+trocr_model = "gg4ever/trOCR-youtube-kor-OCR"
+model = VisionEncoderDecoderModel.from_pretrained(trocr_model).to(device)
+tokenizer = AutoTokenizer.from_pretrained(trocr_model)
+
+pixel_values = (processor(image, return_tensors="pt").pixel_values).to(device)
+generated_ids = model.generate(pixel_values)
+generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(generated_text)
+
+```
+
+## Training Details
+### Training Data
+
+100k words generated by TextRecognitionDataGenerator(trdg) : https://github.com/Belval/TextRecognitionDataGenerator/blob/master/trdg/run.py
+120k words from AI-hub OCR words dataset : https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&dataSetSn=81
+
+### Training Hyperparameters
+
+training_args = Seq2SeqTrainingArguments(
+    predict_with_generate=True,
+    evaluation_strategy="steps",
+    per_device_train_batch_size=32,
+    per_device_eval_batch_size=32,
+    num_train_epochs=2,
+    fp16=True,
+    learning_rate=4e-5,
+    output_dir="./models",
+    save_steps=2000,
+    eval_steps=1000,
+    warmup_steps=2000,
+    weight_decay=0.01
+)