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OpenGVLab/InternVL3_5-1B 를 한국어 멀티모달 데이터로 파인튜닝한 InternVL3.5 specialist.| 항목 | 값 |
|---|---|
| Base model | OpenGVLab/InternVL3_5-1B |
| Method | Full FT |
| Domain | 한국어 종합 347k |
510000 / max 1357523.999999772287927e-05| step | loss |
|---|---|
| 10 | 1.5136 |
| 1010 | 0.7029 |
| 2010 | 0.6294 |
| 3010 | 0.5353 |
| 4010 | 0.4988 |
| 5010 | 0.5090 |
| 6010 | 0.4190 |
| 7010 | 0.4065 |
| 8010 | 0.3964 |
| 9010 | 0.3448 |
| 10000 | 0.3429 |
| subset | repeat |
|---|---|
aihub_visual_ShortQA_30k | 1 |
hf_korLlava_Caption_20k | 1 |
llava_ko_recap_30k | 1 |
out_kor_llava_20k | 1 |
chartRqa1_30k | 1 |
chartRqa2_20k | 1 |
tableVqa_Reason_20k | 1 |
tableVqa_Caption_20k | 1 |
aihub_subjectTxt_OCR_20k | 1 |
aihub_visual_OCR_15k | 1 |
kisti_arxiv_OCR_15k | 1 |
kisti_hanbat_Reason_30k | 1 |
kisti_documen_Reason_10k | 1 |
aihub_mathMultiple_kor_M0 | 1 |
aihub_mathSubjective_kor_M0 | 1 |
kisti_hanbat_Vqa_25k | 1 |
hf_latexUpdate_15k | 1 |
aihub_subjectImg_Parse_10k | 1 |
1from transformers import AutoModel, AutoTokenizer
2import torch
3m = AutoModel.from_pretrained("yujuyeon/internvl3_5-1b-korean-347k", torch_dtype=torch.bfloat16,
4 trust_remote_code=True).eval().cuda()
5tok = AutoTokenizer.from_pretrained("yujuyeon/internvl3_5-1b-korean-347k", trust_remote_code=True, use_fast=False)