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trocr-small-korean

Model Details

TrOCR์€ Encoder-Decoder ๋ชจ๋ธ๋กœ, ์ด๋ฏธ์ง€ ํŠธ๋žœ์Šคํฌ๋จธ ์ธ์ฝ”๋”์™€ ํ…์ŠคํŠธ ํŠธ๋žœ์Šคํฌ๋จธ ๋””์ฝ”๋”๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋ฏธ์ง€ ์ธ์ฝ”๋”๋Š” DeiT ๊ฐ€์ค‘์น˜๋กœ ์ดˆ๊ธฐํ™”๋˜์—ˆ๊ณ , ํ…์ŠคํŠธ ๋””์ฝ”๋”๋Š” ์ž์ฒด์ ์œผ๋กœ ํ•™์Šตํ•œ RoBERTa ๊ฐ€์ค‘์น˜๋กœ ์ดˆ๊ธฐํ™”๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

์ด ์—ฐ๊ตฌ๋Š” ๊ตฌ๊ธ€์˜ TPU Research Cloud(TRC)๋ฅผ ํ†ตํ•ด ์ง€์›๋ฐ›์€ Cloud TPU๋กœ ํ•™์Šต๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

How to Get Started with the Model

import torch

from transformers import VisionEncoderDecoderModel

model = VisionEncoderDecoderModel.from_pretrained("team-lucid/trocr-small-korean")

pixel_values = torch.rand(1, 3, 384, 384)
generated_ids = model.generate(pixel_values)

Training Details

Training Data

ํ•ด๋‹น ๋ชจ๋ธ์€ synthtiger๋กœ ํ•ฉ์„ฑ๋œ 6M๊ฐœ์˜ ์ด๋ฏธ์ง€๋กœ ํ•™์Šต๋˜์—ˆ์Šต๋‹ˆ๋‹ค

Training Hyperparameters

Hyperparameter Small
Warmup Steps 4,000
Learning Rates 1e-4
Batch Size 512
Weight Decay 0.01
Max Steps 500,000
Learning Rate Decay 0.1
Adamฮฒ1Adam\beta_1 0.9
Adamฮฒ2Adam\beta_2 0.98
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