Delete evaluate.py

evaluate.py

@@ -1,26 +0,0 @@
-from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
-from sklearn.metrics import classification_report
-import tensorflow as tf
-import pandas as pd
-
-def get_classification_report():
-    try:
-        # Load test data
-        df = pd.read_csv("test.csv")
-        texts = df["text"].tolist()
-        true_labels = df["label"].tolist()
-
-        # Load tokenizer and model
-        tokenizer = AutoTokenizer.from_pretrained("shrish191/sentiment-bert")
-        model = TFAutoModelForSequenceClassification.from_pretrained("shrish191/sentiment-bert")
-
-        # Tokenize
-        inputs = tokenizer(texts, padding=True, truncation=True, return_tensors="tf")
-        outputs = model(inputs)
-        preds = tf.math.argmax(outputs.logits, axis=1).numpy()
-
-        # Generate report
-        report = classification_report(true_labels, preds, target_names=["negative", "neutral", "positive"])
-        return report
-    except Exception as e:
-        return f"⚠️ Error occurred: {str(e)}"