Update README.md

README.md

@@ -30,7 +30,7 @@ co2_eq_emissions: 100
 
 ## Model Description
 
-We present **QAmemBERT**, which is a [CamemBERT base](https://huggingface.co/camembert-base) fine-tuned for the Question-Answering task for the French language on four French Q&A datasets composed of contexts and questions with their answers inside the context (= SQuAD v1 format) but also contexts and questions with their answers not inside the context (= SQuAD v2 format).
+We present **QAmemBERT**, which is a [CamemBERT base](https://huggingface.co/camembert-base) fine-tuned for the Question-Answering task for the French language on four French Q&A datasets composed of contexts and questions with their answers inside the context (= SQuAD 1.0 format) but also contexts and questions with their answers not inside the context (= SQuAD 2.0 format).
 All these datasets were concatenated into a single dataset that we called [frenchQA](https://huggingface.co/datasets/CATIE-AQ/frenchQA).
 This represents a total of over **221,348 questions/answers pairs used to finetune this model and 6,376 to test it**.
 
@@ -39,14 +39,14 @@ This represents a total of over **221,348 questions/answers pairs used to finetu
 
 | Dataset     | Format      | Train split | Dev split   | Test split  |
 | ----------- | ----------- | ----------- | ----------- | ----------- |
-| [piaf](https://www.data.gouv.fr/en/datasets/piaf-le-dataset-francophone-de-questions-reponses/)| SQuAD v1    | 9 224 Q & A  | X  | X  |  
-| piaf_v2| SQuAD v2    | 9 224 Q & A  | X  | X  |         
-| [fquad](https://fquad.illuin.tech/)| SQuAD v1    | 20 731 Q & A | 3 188 Q & A  (not used in training because it serves as a test dataset) | 2 189 Q & A (not used in our work because not freely available)|         
-| fquad_v2 | SQuAD v2    | 20 731 Q & A | 3 188 Q & A  (not used in training because it serves as a test dataset) | X |         
-| [lincoln/newsquadfr](https://huggingface.co/datasets/lincoln/newsquadfr) | SQuAD v1    | 1 650 Q & A  | 455 Q & A (not used in our work) | X |           
-| lincoln/newsquadfr_v2 | SQuAD v2    | 1 650 Q & A  | 455 Q & A (not used in our work) | X |         
-| [pragnakalp/squad_v2_french_translated](https://huggingface.co/datasets/pragnakalp/squad_v2_french_translated)| SQuAD v2    | 79 069 Q & A  | X  | X  |         
-| pragnakalp/squad_v2_french_translated_v2| SQuAD v2    | 79 069 Q & A  | X  | X  |
+| [piaf](https://www.data.gouv.fr/en/datasets/piaf-le-dataset-francophone-de-questions-reponses/)| SQuAD 1.0   | 9 224 Q & A  | X  | X  |  
+| piaf_v2| SQuAD 2.0    | 9 224 Q & A  | X  | X  |         
+| [fquad](https://fquad.illuin.tech/)| SQuAD 1.0    | 20 731 Q & A | 3 188 Q & A  (not used in training because it serves as a test dataset) | 2 189 Q & A (not used in our work because not freely available)|         
+| fquad_v2 | SQuAD 2.0    | 20 731 Q & A | 3 188 Q & A  (not used in training because it serves as a test dataset) | X |         
+| [lincoln/newsquadfr](https://huggingface.co/datasets/lincoln/newsquadfr) | SQuAD 1.0    | 1 650 Q & A  | 455 Q & A (not used in our work) | X |           
+| lincoln/newsquadfr_v2 | SQuAD 2.0   | 1 650 Q & A  | 455 Q & A (not used in our work) | X |         
+| [pragnakalp/squad_v2_french_translated](https://huggingface.co/datasets/pragnakalp/squad_v2_french_translated)| SQuAD 2.0    | 79 069 Q & A  | X  | X  |         
+| pragnakalp/squad_v2_french_translated_v2| SQuAD 2.0    | 79 069 Q & A  | X  | X  |
 
 All these datasets were concatenated into a single dataset that we called [frenchQA](https://huggingface.co/datasets/CATIE-AQ/frenchQA).
 
@@ -58,44 +58,38 @@ The evaluation was carried out using the [**evaluate**](https://pypi.org/project
 
 ### FQuaD 1.0 (validation)
 
-The metric used is Squad v1.
+The metric used is SQuAD 1.0.
 
 | Model       | Exact_match | F1-score    |
 | ----------- | ----------- | ----------- |
 | [etalab-ia/camembert-base-squadFR-fquad-piaf](https://huggingface.co/etalab-ia/camembert-base-squadFR-fquad-piaf) | 53.60       | 78.09       |
 | QAmembert (previous version)   | 54.26       | 77.87       |
 | QAmembert (**this version**)   | 53.98       | 78.00       |
-| QAmembert-large ♪  | **55.95**       | **81.05**       |
-| [fT0](https://huggingface.co/CATIE-AQ/frenchT0)  | 41.15       | 65.79       |
+| [QAmembert-large](https://huggingface.co/CATIE-AQ/QAmembert-large)  | **55.95**       | **81.05**       |
 
-♪ this model is available on request only
 
 ### qwant/squad_fr (validation)
 
-The metric used is Squad v1.
+The metric used is SQuAD 1.0.
 
 | Model       | Exact_match | F1-score    |
 | ----------- | ----------- | ----------- |
 | [etalab-ia/camembert-base-squadFR-fquad-piaf](https://huggingface.co/etalab-ia/camembert-base-squadFR-fquad-piaf) | 60.17       | 78.27       |
 | QAmembert (previous version)   | 60.40       | 77.27       |
 | QAmembert (**this version**)   |  60.95       | 77.30       |
-| QAmembert-large ♪  | **65.58**       | **81.74**       |
-| [fT0](https://huggingface.co/CATIE-AQ/frenchT0)  | 41.05       | 56.14     |
+| [QAmembert-large](https://huggingface.co/CATIE-AQ/QAmembert-large)   | **65.58**       | **81.74**       |
 
-♪ this model is available on request only.
 
 ### frenchQA
 
-This dataset includes question with no answers in the context. The metric used is Squad v2.
+This dataset includes question with no answers in the context. The metric used is SQuAD 2.0.
 
 | Model       | Exact_match | F1-score    | Answer_f1 | NoAnswer_f1 |
 | ----------- | ----------- | ----------- | ----------- | ----------- |
 | [etalab-ia/camembert-base-squadFR-fquad-piaf](https://huggingface.co/etalab-ia/camembert-base-squadFR-fquad-piaf) | n/a       | n/a       | n/a       | n/a       |
 | QAmembert (previous version)   | 60.28       | 71.29       | 75.92 | 66.65
 | QAmembert (**this version**)   |  **77.14**       | 86.88       | 75.66 | 98.11
-| QAmembert-large ♪  | **77.14**       | **88.74**       | **78.83** | **98.65**
-
-♪ this model is available on request only.
+| [QAmembert-large](https://huggingface.co/CATIE-AQ/QAmembert-large)   | **77.14**       | **88.74**       | **78.83** | **98.65**