musashihinck
commited on
Commit
•
cb4912f
1
Parent(s):
5b48a72
Initial model card
Browse files
README.md
CHANGED
@@ -3,4 +3,57 @@ license_name: gemma-terms
|
|
3 |
license_link: https://ai.google.dev/gemma/terms
|
4 |
language:
|
5 |
- en
|
6 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
license_link: https://ai.google.dev/gemma/terms
|
4 |
language:
|
5 |
- en
|
6 |
+
---
|
7 |
+
|
8 |
+
# LLaVA-Gemma Model Card
|
9 |
+
|
10 |
+
_This model card corresponds to the 2B version of the model with the CLIP-based vision encoder._
|
11 |
+
|
12 |
+
## Overview
|
13 |
+
|
14 |
+
`llava-gemma-2b` is a large multimodal model (LMM) trained using the [LLaVA-v1.5 framework](https://arxiv.org/abs/2310.03744) with the 2-billion parameter `google/gemma-2b-it` model as language backbone.
|
15 |
+
|
16 |
+
## Uses
|
17 |
+
|
18 |
+
The model has been finetuned for multimodal benchmark evaluations, but can also be used as a multimodal chatbot.
|
19 |
+
|
20 |
+
|
21 |
+
## Bias, Risks, and Limitations
|
22 |
+
|
23 |
+
This model has not been assessed for harm or biases, and should not be used for sensitive applications where it may cause harm.
|
24 |
+
|
25 |
+
|
26 |
+
## How to Get Started with the Model
|
27 |
+
|
28 |
+
Using the LLaVA-Gemma models currently requires a custom fork of the [`LLaVA`](https://github.com/haotian-liu/LLaVA) library. _We will release converted checkpoints compatible with the HuggingFace implementation of LLaVA shortly._
|
29 |
+
|
30 |
+
|
31 |
+
|
32 |
+
|
33 |
+
## Training Details
|
34 |
+
|
35 |
+
The `llava-gemma-2b` model was trained on 8 Gaudi 2 accelerators.
|
36 |
+
|
37 |
+
|
38 |
+
### Training Data
|
39 |
+
|
40 |
+
The model was trained using the LLaVA-v1.5 data mixture.
|
41 |
+
|
42 |
+
This is listed as follows:
|
43 |
+
|
44 |
+
- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
|
45 |
+
- 158K GPT-generated multimodal instruction-following data.
|
46 |
+
- 450K academic-task-oriented VQA data mixture.
|
47 |
+
- 40K ShareGPT data.
|
48 |
+
|
49 |
+
|
50 |
+
## Evaluation
|
51 |
+
|
52 |
+
| LM Backbone | Vision Model | Pretrained Connector | GQA | MME cognition | MME perception | MM-Vet | POPE accuracy | POPE F1 | VQAv2 | TextVQA | ScienceQA Image | MMVP |
|
53 |
+
| ------------ | ------------- | --------------------- | ------ | ---------------- | ----------------- | ------- | ------------------ | ------------ | ------ | -------- | -------------------- | ------ |
|
54 |
+
| gemma-2b-it | CLIP | Yes | 0.531 | 236.071 | 1130.492 | 17.706 | 0.850 | 0.839 | 70.65 | 28.06 | 0.564 | 0.287 |
|
55 |
+
| gemma-2b-it | CLIP | No | 0.481 | 247.857 | 934.611 | 13.119 | 0.784 | 0.762 | 61.74 | | 0.549 | 0.180 |
|
56 |
+
| gemma-7b-it | CLIP | Yes | 0.472 | 253.571 | 894.910 | 18.165 | 0.848 | 0.829 | 68.7 | | 0.625 | 0.327 |
|
57 |
+
| gemma-7b-it | CLIP | No | 0.472 | 278.214 | 857.274 | 19.083 | 0.782 | 0.734 | 65.09 | | 0.636 | 0.240 |
|
58 |
+
| gemma-2b-it | DinoV2 | Yes | 0.587 | 307.143 | 1132.970 | 19.128 | 0.853 | 0.838 | 71.37 | 12.53 | 0.555 | 0.227 |
|
59 |
+
| gemma-2b-it | DinoV2 | No | 0.501 | 308.929 | 959.351 | 14.541 | 0.793 | 0.772 | 61.65 | 11.1 | 0.568 | 0.180 |
|