Update README.md

README.md

@@ -35,11 +35,12 @@ Our methodology is described in a blog post available in [English](https://blog.
 ## Dataset
 
 The dataset used is [frenchNER_4entities](https://huggingface.co/datasets/CATIE-AQ/frenchNER_4entities), which represents ~385k sentences labeled in 4 categories:
-* PER: personality ;
-* LOC: location ;
-* ORG: organization ;
-* MISC: miscellaneous  ;
-* O: background (Outside entity).
+| Label | Examples                                                   |
+|:------|:-----------------------------------------------------------|
+| PER   | "La Bruyère", "Gaspard de Coligny", "Wittgenstein"         |
+| ORG   | "UTBM", "American Airlines", "id Software"                 |
+| LOC   | "République du Cap-Vert", "Créteil", "Bordeaux"            |
+| MISC  | "Wolfenstein 3D", "Révolution française", "Coupe du monde" |
 
 The distribution of the entities is as follows:
 
@@ -103,11 +104,67 @@ The evaluation was carried out using the [**evaluate**](https://pypi.org/project
 </thead>
 <tbody>
     <tr>
+        <td rowspan="3"><br><a href="https://hf.co/Jean-Baptiste/camembert-ner">Jean-Baptiste/camembert-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.952</td>
+        <td><br>0.924</td>
+        <td><br>0.870</td>
+        <td><br>0.845</td>
+        <td><br>0.986</td>
+        <td><br>0.976</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.990</td>
+        <td><br>0.972</td>
+        <td><br>0.938</td>
+        <td><br>0.546</td>
+        <td><br>0.992</td>
+        <td><br>0.976</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.971</td>
+        <td><br>0.947</td>
+        <td><br>0.902</td>
+        <td><br>0.663</td>
+        <td><br>0.989</td>
+        <td><br>0.976</td>
+    </tr>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf/cmarkea/distilcamembert-base-ner">cmarkea/distilcamembert-base-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.962</td>
+        <td><br>0.933</td>
+        <td><br>0.857</td>
+        <td><br>0.830</td>
+        <td><br>0.985</td>
+        <td><br>0.976</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.987</td>
+        <td><br>0.963</td>
+        <td><br>0.930</td>
+        <td><br>0.545</td>
+        <td><br>0.993</td>
+        <td><br>0.976</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.974</td>
+        <td><br>0.948</td>
+        <td><br>0.892</td>
+        <td><br>0.658</td>
+        <td><br>0.989</td>
+        <td><br>0.976</td>
+    </tr>
+      <tr>
         <td rowspan="3"><br>Camembert-base-frenchNER_4entities</td>
         <td><br>Precision</td>
         <td><br>0.973</td>
         <td><br>0.951</td>
-        <td><br>0.8877</td>
+        <td><br>0.888</td>
         <td><br>0.850</td>
         <td><br>0.993</td>
         <td><br>0.984</td>
@@ -123,12 +180,12 @@ The evaluation was carried out using the [**evaluate**](https://pypi.org/project
     </tr>
     <tr>
         <td>F1</td>
-        <td><br>0.978</td>
-        <td><br>0.958</td>
-        <td><br>0.903</td>
-        <td><br>0.814</td>
-        <td><br>0.993</td>
-        <td><br>0.984</td>
+        <td><br><b>0.978</b></td>
+        <td><br><b>0.958</b></td>
+        <td><br><b>0.903</b></td>
+        <td><br><b>0.814</b></td>
+        <td><br><b>0.993</b></td>
+        <td><br><b>0.984</b></td>
     </tr>
 </tbody>
 </table>
@@ -152,12 +209,68 @@ In detail:
     </tr>
 </thead>
 <tbody>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf.co/Jean-Baptiste/camembert-ner">Jean-Baptiste/camembert-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.908</td>
+        <td><br>0.717</td>
+        <td><br>0.753</td>
+        <td><br>0.620</td>
+        <td><br>0.936</td>
+        <td><br>0.889</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.975</td>
+        <td><br>0.811</td>
+        <td><br>0.696</td>
+        <td><br>0.511</td>
+        <td><br>0.938</td>
+        <td><br>0.889</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.940</td>
+        <td><br>0.761</td>
+        <td><br>0.723</td>
+        <td><br>0.560</td>
+        <td><br>0.937</td>
+        <td><br>0.889</td>
+    </tr>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf/cmarkea/distilcamembert-base-ner">cmarkea/distilcamembert-base-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.885</td>
+        <td><br>0.738</td>
+        <td><br>0.737</td>
+        <td><br>0.589</td>
+        <td><br>0.928</td>
+        <td><br>0.881</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.960</td>
+        <td><br>0.759</td>
+        <td><br>0.655</td>
+        <td><br>0.482</td>
+        <td><br>0.939</td>
+        <td><br>0.881</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.921</td>
+        <td><br>0.748</td>
+        <td><br>0.694</td>
+        <td><br>0.530</td>
+        <td><br>0.934</td>
+        <td><br>0.881</td>
+    </tr>
     <tr>
         <td rowspan="3"><br>Camembert-base-frenchNER_4entities</td>
         <td><br>Precision</td>
         <td><br>0.954</td>
         <td><br>0.893</td>
-        <td><br>0.851/td>
+        <td><br>0.851</td>
         <td><br>0.849</td>
         <td><br>0.979</td>
         <td><br>0.954</td>
@@ -165,7 +278,7 @@ In detail:
     <tr>
         <td><br>Recall</td>
         <td><br>0.967</td>
-        <td><br>0.887/td>
+        <td><br>0.887</td>
         <td><br>0.883</td>
         <td><br>0.855</td>
         <td><br>0.974</td>
@@ -173,12 +286,12 @@ In detail:
     </tr>
     <tr>
         <td>F1</td>
-        <td><br>0.960</td>
-        <td><br>0.890</td>
-        <td><br>0.867</td>
-        <td><br>0.852</td>
-        <td><br>0.977</td>
-        <td><br>0.954</td>
+        <td><br><b>0.960</b></td>
+        <td><br><b>0.890</b></td>
+        <td><br><b>0.867</b></td>
+        <td><br><b>0.852</b></td>
+        <td><br><b>0.977</b></td>
+        <td><br><b>0.954</b></td>
     </tr>
 </tbody>
 </table>
@@ -199,6 +312,62 @@ In detail:
     </tr>
 </thead>
 <tbody>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf.co/Jean-Baptiste/camembert-ner">Jean-Baptiste/camembert-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.931</td>
+        <td><br>0.893</td>
+        <td><br>0.827</td>
+        <td><br>0.725</td>
+        <td><br>0.979</td>
+        <td><br>0.966</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.994</td>
+        <td><br>0.980</td>
+        <td><br>0.959</td>
+        <td><br>0.295</td>
+        <td><br>0.990</td>
+        <td><br>0.966</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.962</td>
+        <td><br>0.934</td>
+        <td><br>0.888</td>
+        <td><br>0.419</td>
+        <td><br>0.984</td>
+        <td><br>0.966</td>
+    </tr>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf/cmarkea/distilcamembert-base-ner">cmarkea/distilcamembert-base-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.954</td>
+        <td><br>0.908</td>
+        <td><br>0.817</td>
+        <td><br>0.705</td>
+        <td><br>0.977</td>
+        <td><br>0.967</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.991</td>
+        <td><br>0.969</td>
+        <td><br>0.963</td>
+        <td><br>0.310</td>
+        <td><br>0.990</td>
+        <td><br>0.967</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.972</td>
+        <td><br>0.938</td>
+        <td><br>0.884</td>
+        <td><br>0.430</td>
+        <td><br>0.984</td>
+        <td><br>0.967</td>
+    </tr>
     <tr>
         <td rowspan="3"><br>Camembert-base-frenchNER_4entities</td>
         <td><br>Precision</td>
@@ -220,12 +389,12 @@ In detail:
     </tr>
     <tr>
         <td>F1</td>
-        <td><br>0.985</td>
-        <td><br>0.973</td>
-        <td><br>0.938</td>
-        <td><br>0.770</td>
-        <td><br>0.992</td>
-        <td><br>0.983</td>
+        <td><br><b>0.985</b></td>
+        <td><br><b>0.973</b></td>
+        <td><br><b>0.938</b></td>
+        <td><br><b>0.770</b></td>
+        <td><br><b>0.992</b></td>
+        <td><br><b>0.983</b></td>
     </tr>
 </tbody>
 </table>
@@ -247,6 +416,62 @@ In detail:
     </tr>
 </thead>
 <tbody>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf.co/Jean-Baptiste/camembert-ner">Jean-Baptiste/camembert-ner</a></td>
+        <td><br>Precision</td>
+        <td><br><b>0.986</b></td>
+        <td><br><b>0.962</b></td>
+        <td><br><b>0.925</b></td>
+        <td><br><b>0.943</b></td>
+        <td><br><b>0.998</b></td>
+        <td><br><b>0.992</b></td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br><b>0.987</b></td>
+        <td><br><b>0.969</b></td>
+        <td><br><b>0.951</b></td>
+        <td><br><b>0.933</b></td>
+        <td><br><b>0.997</b></td>
+        <td><br><b>0.992</b></td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br><b>0.986</b></td>
+        <td><br><b>0.966</b></td>
+        <td><br><b>0.938</b></td>
+        <td><br><b>0.938</b></td>
+        <td><br><b>0.998</b></td>
+        <td><br><b>0.992</b></td>
+    </tr>
+      <tr>
+        <td rowspan="3"><br><a href="https://hf/cmarkea/distilcamembert-base-ner">cmarkea/distilcamembert-base-ner</a></td>
+        <td><br>Precision</td>
+        <td><br>0.982</td>
+        <td><br>0.951</td>
+        <td><br>0.910</td>
+        <td><br>0.942</td>
+        <td><br>0.997</td>
+        <td><br>0.991</td>
+    </tr>
+    <tr>
+        <td><br>Recall</td>
+        <td><br>0.985</td>
+        <td><br>0.963</td>
+        <td><br>0.940</td>
+        <td><br>0.910</td>
+        <td><br>0.998</td>
+        <td><br>0.991</td>
+    </tr>
+    <tr>
+        <td>F1</td>
+        <td><br>0.983</td>
+        <td><br>0.964</td>
+        <td><br>0.925</td>
+        <td><br>0.926</td>
+        <td><br>0.997</td>
+        <td><br>0.991</td>
+    </tr>
     <tr>
         <td rowspan="3"><br>Camembert-base-frenchNER_4entities</td>
         <td><br>Precision</td>