Update README.md

README.md

@@ -29,16 +29,19 @@ tags:
 
 ## Performance
 
+
 | Model | Avg. | ESG Restaurant Human | Econ Macro Multi. | AXA Multi. | MIT Bio | ESG Restaurant Synth. | ESG Restaurant Synth. Multi. | MIT Bio Multi. | AXA | Econ. Macro |
 |-------|------|----------------------|-------------------|------------|---------|----------------------|----------------------------|---------------|-----|------------|
-| ColNomic Embed Multimodal 7B | 61.6 | 67.1 | 54.9 | 59.7 | 66.1 | 58.1 | 56.9 | 64.3 | 67.4 | 59.6 |
+| ColNomic Embed Multimodal 7B | 62.7 | 73.9 | 54.7 | 61.3 | 66.1 | 57.3 | 56.7 | 64.2 | 68.3 | 61.6 |
 | ColNomic Embed Multimodal 3B | 61.2 | 65.8 | 55.4 | 61.0 | 63.5 | 56.6 | 57.2 | 62.5 | 68.8 | 60.2 |
 | T-Systems ColQwen2.5-3B | 59.9 | 72.1 | 51.2 | 60.0 | 65.3 | 51.7 | 53.3 | 61.7 | 69.3 | 54.8 |
 | Nomic Embed Multimodal 7B | 59.7 | 65.7 | 57.7 | 59.3 | 64.0 | 49.2 | 51.9 | 61.2 | 66.3 | 63.1 |
+| GME Qwen2 7B | 59.0 | 65.8 | 56.2 | 55.4 | 64.0 | 54.3 | 56.7 | 55.1 | 60.7 | 62.9 |
 | **Nomic Embed Multimodal 3B** | 58.8 | 59.8 | 57.5 | 58.8 | 62.5 | 49.4 | 49.4 | 58.6 | 69.6 | 63.5 |
 | Llama Index vdr-2b-multi-v1 | 58.4 | 63.1 | 52.8 | 61.0 | 60.6 | 50.3 | 51.2 | 56.9 | 68.8 | 61.2 |
 | Voyage Multimodal 3 | 55.0 | 56.1 | 55.0 | 59.5 | 56.4 | 47.2 | 46.2 | 51.5 | 64.1 | 58.8 |
 
+
 ## Model Architecture
 
 - **Total Parameters**: 3B
@@ -78,7 +81,6 @@ Nomic Embed Multimodal 3B was developed through several key innovations:
 
 3. **Positive-aware Hard Negative Mining**: Reducing false negatives using techniques introduced in NV-Retriever.
 
-4. **Multi-Vector Configuration**: Providing a multi-vector variant that achieves higher performance than the dense variant.
 
 ## Limitations