Udate LR model

tasks/text.py

@@ -2,14 +2,16 @@ from fastapi import APIRouter
 from datetime import datetime
 from datasets import load_dataset
 from sklearn.metrics import accuracy_score
-import random
+from sklearn.linear_model import LogisticRegression
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.model_selection import train_test_split
 
 from .utils.evaluation import TextEvaluationRequest
 from .utils.emissions import tracker, clean_emissions_data, get_space_info
 
 router = APIRouter()
 
-DESCRIPTION = "Random Baseline"
+DESCRIPTION = "Logistic Regression"
 ROUTE = "/text"
 
 @router.post(ROUTE, tags=["Text Task"], 
@@ -24,11 +26,8 @@ async def evaluate_text(request: TextEvaluationRequest):
     # Get space info
     username, space_url = get_space_info()
 
-    from sklearn.linear_model import LogisticRegression
-    from sklearn.feature_extraction.text import TfidfVectorizer
-    from sklearn.model_selection import train_test_split
-    from sklearn import metrics
-    from datetime import datetime
+
+
 
     # Define the label mapping
     LABEL_MAPPING = {
@@ -53,9 +52,6 @@ async def evaluate_text(request: TextEvaluationRequest):
     train_test = dataset["train"].train_test_split(test_size=request.test_size, seed=request.test_seed)
     test_dataset = train_test["test"]
 
-    #test_dataset = train_test["test"]
-    #train_dataset = train_test["train"]
-
     tfidf_vect = TfidfVectorizer(stop_words = 'english')
     
     tfidf_train = tfidf_vect.fit_transform(train_dataset['quote'])