Update README.md

README.md

@@ -80,6 +80,8 @@ def preprocess_text(text):
 
 
 # Step 3: Load the model and tokenizer from Hugging Face Hub
+This step loads the pre-trained model and tokenizer, which are hosted on the Hugging Face Hub. 
+
 ```python
 print("Loading model and tokenizer...")
 REPO_NAME = "CIS5190GoGo/CustomModel" #This is where we pushed the model to
@@ -94,7 +96,7 @@ print("Model and tokenizer loaded successfully!")
 # Step 4: Load test dataset
 ```python
 print("Loading test data...")
-test_data_path = "/content/drive/MyDrive/5190_project/test_data_random_subset.csv"  # Replace with your test set path
+test_data_path = "Replace wit your test set path" #Note: Replace with your test set path
 test_data = pd.read_csv(test_data_path)
 ```
 # Step 5: Preprocess test data
@@ -129,4 +131,30 @@ with torch.no_grad():
 
 accuracy = accuracy_score(all_labels, all_preds)
 print(f"Test Accuracy: {accuracy:.4f}")
+```
+# Expected output:
+```python
+Loading model and tokenizer...
+/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: 
+The secret `HF_TOKEN` does not exist in your Colab secrets.
+To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.
+You will be able to reuse this secret in all of your notebooks.
+Please note that authentication is recommended but still optional to access public models or datasets.
+  warnings.warn(
+config.json: 100%
+ 735/735 [00:00<00:00, 40.8kB/s]
+model.safetensors: 100%
+ 499M/499M [00:11<00:00, 42.7MB/s]
+tokenizer_config.json: 100%
+ 1.19k/1.19k [00:00<00:00, 69.8kB/s]
+vocab.json: 100%
+ 999k/999k [00:00<00:00, 4.09MB/s]
+merges.txt: 100%
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+special_tokens_map.json: 100%
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+Model and tokenizer loaded successfully!
+Loading test data...
+Evaluating the model...
+Test Accuracy: 0.8500
 ```