Update README.md

README.md

@@ -28,12 +28,29 @@ Training methodology ... is a bit of a mess, trying out different things.
 I'm adding the datasets used at any point, but I don't think replicating the recipe is doable or sensible.
 
 Original upscale at Lambent/danube2-upscale-1, duplicating layers 16-21. Various training methods attempted to repair.
-
+Linear merge is of the 4 that were at least 90% parseable by the EQ-Bench benchmark.
 
 |                                  Model                                  |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
 |-------------------------------------------------------------------------|------:|------:|---------:|-------:|------:|
 |[danube2-upscale-1.7](https://huggingface.co/Lambent/danube2-upscale-1.7)|  27.97|  62.16|      42.2|    32.2|  41.13|
 
+|                                  Model                                  |EQ-Bench|Average|
+|-------------------------------------------------------------------------|-------:|------:|
+|[danube2-upscale-1.7](https://huggingface.co/Lambent/danube2-upscale-1.7)|   15.52|  15.52|
+
+### EQ-Bench
+|  Task  |Version|           Metric            | Value  |   |Stderr|
+|--------|------:|-----------------------------|--------|---|------|
+|eq_bench|    2.1|eqbench,none                 |   15.52|   |      |
+|        |       |eqbench_stderr,none          |    2.77|   |      |
+|        |       |percent_parseable,none       |     100|   |      |
+|        |       |percent_parseable_stderr,none|       0|   |      |
+|        |       |alias                        |eq_bench|   |      |
+
+Average: 15.52%
+
+Average score: 15.52%
+
 ## Merge Details
 ### Merge Method