update_tables (#10)

- add more complete fairness tables (7fd64927c3ce647768437994520a430c591254bc)
- fix detailed table column names (87c2f77a278c891d13ffd8e5186aa6f7d8e0146c)
- update fairness std (00e118310a5d2ac41591682f4c544aaab4dcfded)
- have model name display in one line (d93d37c6d83075998adaec704de25b9ac935fd59)
- take off detailed fairness table (a5cbcec72482ec5f9dbe1d5f6595a0c6b7575871)
- add per bucket std description (21d0413d703dba0a93bb091d9bb1c0a929df7fdc)

README.md

@@ -274,13 +274,13 @@ Similarly to the base IDEFICS models, we performed checkpoint selection to stop
 | 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) |
+| <nobr>IDEFICS 80B Instruct<br> | 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) | - |
 |  | 16 | 68.6 (3.2) | 58.2 (1.4) | 39.1 (2.8) | 48.7 (0.4) | 77.0 (-4.5) | 120.5 (4.0) | 107.4 (0.4) | 76.0 (-4.1) | - | 56.4 (0.7) | - | 70.1 (2.4) | - |
 |  | 32 | 68.8 (2.9) | 59.5 (1.8) | 39.3 (2.6) | 51.2 (1.2) | 79.7 (-3.0) | 123.2 (6.5) | 108.4 (1.0) | 78.4 (-2.7) | - | 54.9 (2.4) | - | 70.5 (3.2) | - |
 <br>
-| IDEFICS 9B Instruct | 0 | 65.8 (15.0) | 46.1 (7.6) | 29.2 (3.3) | 41.2 (5.6) | 67.1 (41.7) | 129.1 (83.0) | 101.1 (64.3) | 71.9 (44.6) | 49.2 (0.5) | 53.5 (1.8) | 60.6 (16.4) | 62.8 (1.0) | 5.8/20.0/18.0 (0.8/2.2/-2.8)|
+| <nobr>IDEFICS 9B Instruct<br> | 0 | 65.8 (15.0) | 46.1 (7.6) | 29.2 (3.3) | 41.2 (5.6) | 67.1 (41.7) | 129.1 (83.0) | 101.1 (64.3) | 71.9 (44.6) | 49.2 (0.5) | 53.5 (1.8) | 60.6 (16.4) | 62.8 (1.0) | 5.8/20.0/18.0 (0.8/2.2/-2.8)|
 |  | 4 | 66.2 (10.8) | 48.7 (3.3) | 31.0 (3.4) | 39.0 (2.1) | 68.2 (8.2) | 128.2 (35.1) | 100.9 (19.6) | 74.8 (15.0) | 48.9 (1.0) | 51.8 (1.1) | 53.8 (16.4) | 60.6 (-1.8) | - |
 |  | 8 | 66.5 (10.2) | 50.8 (3.1) | 31.0 (3.5) | 41.9 (1.6) | 70.0 (6.7) | 128.8 (31.8) | 101.5 (14.8) | 75.5 (13.6) | 48.2 (0.6) | 51.7 (0.6) | - | 61.3 (-4.9) | - |
 |  | 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) | - |
@@ -358,13 +358,14 @@ The [notebook](https://huggingface.co/spaces/HuggingFaceM4/m4-bias-eval/blob/mai
 
 Besides, we also computed the classification accuracy on FairFace for both the base and instructed models:
 
-| Model | Shots | <nobr>FairFace - Gender<br>acc.</nobr> | <nobr>FairFace - Race<br>acc.</nobr> | <nobr>FairFace - Age<br>acc.</nobr> |
-|:---------------------|--------:|----------------------------:|--------------------------:|-------------------------:|
-| IDEFICS 80B          |       0 |                        95.8 |                      64.1 |                     51.0 |
-| IDEFICS 9B           |       0 |                        94.4 |                      55.3 |                     45.1 |
-| IDEFICS 80B Instruct |       0 |                        95.7 |                      63.4 |                     47.1 |
-| IDEFICS 9B Instruct  |       0 |                        92.7 |                      59.6 |                     43.9 |
+| Model | Shots | <nobr>FairFaceGender<br>acc. (std*)</nobr> | <nobr>FairFaceRace<br>acc. (std*)</nobr> | <nobr>FairFaceAge<br>acc. (std*)</nobr> |
+| :--------------------- | --------: | ----------------------------: | --------------------------: | -------------------------: |
+| IDEFICS 80B | 0 | 95.8 (1.0) | 64.1 (16.1) | 51.0 (2.9) |
+| IDEFICS 9B | 0 | 94.4 (2.2) | 55.3 (13.0) | 45.1 (2.9) |
+| IDEFICS 80B Instruct | 0 | 95.7 (2.4) | 63.4 (25.6) | 47.1 (2.9) |
+| IDEFICS 9B Instruct | 0 | 92.7 (6.3) | 59.6 (22.2) | 43.9 (3.9) |
 
+*Per bucket standard deviation. Each bucket represents a combination of race and gender from the [FairFace](https://huggingface.co/datasets/HuggingFaceM4/FairFace) dataset.
 ## Other limitations
 
 - The model currently will offer medical diagnosis when prompted to do so. For example, the prompt `Does this X-ray show any medical problems?` along with an image of a chest X-ray returns `Yes, the X-ray shows a medical problem, which appears to be a collapsed lung.`