add column to distinguish dataset part of finetuning mix

README.md

@@ -287,8 +287,9 @@ Fairness Evaluations:
 Similarly to the base IDEFICS models, we performed checkpoint selection to stop the training. Given that M3IT contains in the training set a handful of the benchmarks we were evaluating on, we used [MMBench](https://huggingface.co/papers/2307.06281) as a held-out validation benchmark to perform checkpoint selection. We select the checkpoint at step 3'000 for IDEFICS-80b-instruct and at step 8'000 for IDEFICS-9b-instruct.
 
 Idefics Instruct Evaluations:
-| Model | Shots | <nobr>VQAv2* <br>OE VQA acc.</nobr> | <nobr>OKVQA* <br>OE VQA acc.</nobr> | <nobr>TextVQA* <br>OE VQA acc.</nobr> | <nobr>VizWiz<br>OE VQA acc.</nobr> | <nobr>TextCaps* <br>CIDEr</nobr> | <nobr>Coco* <br>CIDEr</nobr> | <nobr>NoCaps<br>CIDEr</nobr> | <nobr>Flickr<br>CIDEr</nobr> | <nobr>VisDial* <br>NDCG</nobr> | <nobr>HatefulMemes<br>ROC AUC</nobr> | <nobr>ScienceQA* <br>acc.</nobr> | <nobr>RenderedSST2<br>acc.</nobr> | <nobr>Winoground<br>group (text/image)</nobr> |
+| Model | Shots | <nobr>VQAv2 <br>OE VQA acc.</nobr> | <nobr>OKVQA <br>OE VQA acc.</nobr> | <nobr>TextVQA <br>OE VQA acc.</nobr> | <nobr>VizWiz<br>OE VQA acc.</nobr> | <nobr>TextCaps <br>CIDEr</nobr> | <nobr>Coco <br>CIDEr</nobr> | <nobr>NoCaps<br>CIDEr</nobr> | <nobr>Flickr<br>CIDEr</nobr> | <nobr>VisDial <br>NDCG</nobr> | <nobr>HatefulMemes<br>ROC AUC</nobr> | <nobr>ScienceQA <br>acc.</nobr> | <nobr>RenderedSST2<br>acc.</nobr> | <nobr>Winoground<br>group (text/image)</nobr> |
 | :--------------------- | --------: | ---------------------: | ---------------------: | -----------------------: | ----------------------: | -------------------: | ---------------: | -----------------: | -----------------: | -----------------: | -------------------------: | -----------------------: | --------------------------: | ----------------------------------: |
+| Finetuning data does not contain dataset | - | &#10060; | &#10060; | &#10060; | &#10004; | &#10060; | &#10060; | &#10004; | &#10004; | &#10060; | &#10004; | &#10060; | &#10004; | &#10060; |
 | IDEFICS 80B Instruct | 0 | 37.4 (-22.7) | 36.9 (-8.2) | 32.9 (1.9) | 26.2 (-9.8) | 76.5 (19.7) | 117.2 (25.4) | 104.5 (39.5) | 65.3 (11.7) | 49.3 (0.4) | 58.9 (-1.7) | 69.5 (0.5) | 67.3 (6.8) | 9.2/20.0/25.0 (1.2/1.2/2.5) |
 |  | 4 | 67.5 (4.0) | 54.0 (1.7) | 37.8 (3.5) | 39.8 (-0.7) | 71.7 (-1.0) | 116.9 (6.6) | 104.0 (4.4) | 67.1 (-6.6) | 48.9 (0.5) | 57.5 (-0.3) | 60.5 (1.6) | 65.5 (-1.1) | - |
 |  | 8 | 68.1 (3.4) | 56.9 (1.8) | 38.2 (2.5) | 44.8 (-1.3) | 72.7 (-4.9) | 116.8 (2.5) | 104.8 (-0.9) | 70.7 (-5.9) | 48.2 (0.3) | 58.0 (-0.2) | - | 68.6 (0.8) | - |
@@ -301,7 +302,6 @@ Idefics Instruct Evaluations:
 |  | 16 | 66.8 (9.8) | 51.7 (3.3) | 31.6 (3.7) | 44.8 (2.3) | 70.2 (2.7) | 128.8 (29.1) | 101.5 (12.2) | 75.8 (11.4) | - | 51.7 (0.7) | - | 63.3 (-4.6) | - |
 |  | 32 | 66.9 (9.0) | 52.3 (2.7) | 32.0 (3.7) | 46.0 (2.2) | 71.7 (3.6) | 127.8 (29.8) | 101.0 (10.5) | 76.3 (11.9) | - | 50.8 (1.0) | - | 60.9 (-6.1) | - |
 
-*Starred evaluations are also part of the intsruction data mix
   
 Fairness Evaluations:
 | Model | Shots | <nobr>FairFaceGender<br>acc.</nobr> | <nobr>FairFaceRace<br>acc.</nobr> | <nobr>FairFaceAge<br>acc.</nobr> |