Update README.md

README.md

@@ -13,32 +13,44 @@ model-index:
   results: []
 ---
 
-<!-- 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. -->
+# Identify Clickbait Articles
 
-# classify-clickbait-titll
-
-This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0173
-- Accuracy: 0.9951
-- F1: 0.9951
-- Precision: 0.9951
-- Recall: 0.9951
-- Accuracy Label Clickbait: 0.9866
-- Accuracy Label Factual: 1.0
+This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on a synthetic dataset with 65% factual article titles and 35% clickbait articles.
 
 ## Model description
 
-More information needed
+Built to identify factual vs clickbait titles.
 
 ## Intended uses & limitations
 
-More information needed
+Use it on any title to understand how the model is interpreting the title, whether it is factual or clickbait. 
+
+Go ahead and try a few of your own. 
+
+Here are a few examples:
+
+**Title:** A Comprehensive Guide for Getting Started with Hugging Face
+**Output:** Factual
+
+**Title:** OpenAI GPT-4o: The New Best AI Model in the World. Like in the Movies. For Free
+**Output:** Clickbait
+
+**Title:** GPT4 Omni — So much more than just a voice assistant
+**Output:** Clickbait
+
+**Title:** Building Vector Databases with FastAPI and ChromaDB
+**Output:** Factual
 
 ## Training and evaluation data
 
-More information needed
+It achieves the following results on the evaluation set:
+- Loss: 0.0173
+- Accuracy: 0.9951
+- F1: 0.9951
+- Precision: 0.9951
+- Recall: 0.9951
+- Accuracy Label Clickbait: 0.9866
+- Accuracy Label Factual: 1.0
 
 ## Training procedure
 
@@ -56,18 +68,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 500
 - num_epochs: 3
 
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Accuracy Label Clickbait | Accuracy Label Factual |
-|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------------------------:|:----------------------:|
-| 0.0561        | 0.4831 | 100  | 0.0488          | 0.9927   | 0.9927 | 0.9927    | 0.9927 | 0.9933                   | 0.9923                 |
-| 0.0037        | 0.9662 | 200  | 0.0097          | 0.9988   | 0.9988 | 0.9988    | 0.9988 | 0.9967                   | 1.0                    |
-| 0.0012        | 1.4493 | 300  | 0.0016          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                      | 1.0                    |
-| 0.0012        | 1.9324 | 400  | 0.0016          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                      | 1.0                    |
-| 0.0433        | 2.4155 | 500  | 0.0020          | 0.9988   | 0.9988 | 0.9988    | 0.9988 | 0.9967                   | 1.0                    |
-| 0.0003        | 2.8986 | 600  | 0.0167          | 0.9951   | 0.9951 | 0.9951    | 0.9951 | 0.9866                   | 1.0                    |
-
-
 ### Framework versions
 
 - Transformers 4.41.0