Update ModelCard

README.md

@@ -6,29 +6,40 @@ tags:
 model-index:
 - name: xlm-roberta-base-finetuned-panx-it
   results: []
+language:
+- it
+metrics:
+- f1
+library_name: transformers
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
 # xlm-roberta-base-finetuned-panx-it
 
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base).
 It achieves the following results on the evaluation set:
 - Loss: 0.2619
 - F1 Score: 0.8321
 
 ## Model description
 
-More information needed
+This model is a fine-tuned version of xlm-roberta-base on the Italian subset of the PAN-X dataset for Named Entity Recognition (NER). The model has been fine-tuned to perform token classification tasks and is evaluated on its performance in identifying named entities in Italian text.
 
 ## Intended uses & limitations
 
-More information needed
+### Intended uses:
+
+Named Entity Recognition (NER) tasks specifically for Italian.
+Token classification tasks involving Italian text.
+
+### Limitations:
+
+The model's performance is optimized for Italian and may not generalize well to other languages without further fine-tuning.
+The model's predictions are based on the data it was trained on and may not handle out-of-domain data as effectively.
 
 ## Training and evaluation data
 
-More information needed
+The model was fine-tuned on the Italian subset of the PAN-X dataset, which includes labeled examples of named entities in Italian text. The evaluation data is a separate portion of the same dataset, used to assess the model's performance.
 
 ## Training procedure
 
@@ -57,4 +68,4 @@ The following hyperparameters were used during training:
 - Transformers 4.41.1
 - Pytorch 2.3.0+cu121
 - Datasets 2.19.1
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1