add sbert

tasks/text.py

@@ -20,10 +20,11 @@ DESCRIPTION = "Random Baseline"
 ROUTE = "/text"
 
 models_descriptions = {
-    "baseline": "random baseline",
-    "tfidf_xgb": "TF-IDF vectorizer and XGBoost classifier",
-    "bert_base_pruned": "Pruned BERT base model",
-    'climate_bert_pruned': "Fine-tuned and pruned DistilRoBERTa pre-trained on climate texts"
+    "baseline": "random baseline", # Baseline
+    "tfidf_xgb": "TF-IDF vectorizer and XGBoost classifier", # Submitted
+    "bert_base_pruned": "Pruned BERT base model", # Submitted
+    'climate_bert_pruned': "Fine-tuned and pruned DistilRoBERTa pre-trained on climate texts", # Not working
+    "sbert_distilroberta": "Fine-tuned sentence transformer DistilRoBERTa"
 }
 
 
@@ -109,7 +110,7 @@ def bert_classifier(test_dataset: dict, model: str):
 
 @router.post(ROUTE, tags=["Text Task"])
 async def evaluate_text(request: TextEvaluationRequest,
-                        model: str = "climate_bert_pruned"):
+                        model: str = "sbert_distilroberta"):
     """
     Evaluate text classification for climate disinformation detection.