How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites - Githubissues

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How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites #27

Open hjeun opened 6 months ago

hjeun commented 6 months ago

https://arxiv.org/abs/2404.16821

Closed source 모델보다 우수

성능 개선의 중요한 3가지 요소
- Strong Vision Encoder: InterViT-6B
- Dynamic High Resolution: Tile 4K based on 448x448 and preserve aspect ratio
- High-Quality Bilingual Dataset

InterViT-6B (Continuous pre-training)
- 1. InternViT-6B: 224, CLIP 학습
- 1. InternViT-6B-448px-V1.2: 448, Nous-Hermes-2-Yi-34B 붙여서 학습
- 1. InternViT-6B-448px-V1.5: 448 Tiles ranging from 1 to 12, InternLM2-20B 붙여서 학습
InternLM2-20B
Dynamic High-Resolution
- Dynamic Aspect Ratio Matching
- Aspect Ration Preserving
- Training visual tokens from 256 to 3,328, Testing visual tokens maximum of 10,496
Pixel Shuffle이 뭐지?
Context Length 4096

OCR datasets 많이 넣음
PaddleOCR 사용

EN dataset translation to ZH
GPT 사용

tile 평균 24가 성능 제일 좋음