Update README.md

README.md

@@ -1,32 +1,30 @@
 ---
-license: mit
----
-# Step 3: Create a comprehensive model card (README.md)
-model_card = f"""---
 language: en
 license: apache-2.0
 tags:
-- text-classification
-- education
-- taxonomy
-- dave-psychomotor
-- learning-objectives
+  - text-classification
+  - education
+  - taxonomy
+  - dave-psychomotor
+  - learning-objectives
+  - motor-skills
 datasets:
-- custom
+  - custom
 metrics:
-- accuracy
-- f1
+  - accuracy
+  - f1
 widget:
-- text: "Students will observe and replicate the proper hand positioning during violin lessons"
-  example_title: "Imitation Example"
-- text: "Learners will perform the CPR procedure following the training manual guidelines"
-  example_title: "Manipulation Example"
-- text: "Nurses will accurately draw 5mL of medication into a syringe with 0.1mL precision"
-  example_title: "Precision Example"
-- text: "Physical therapists will coordinate breathing patterns with stride rhythm"
-  example_title: "Articulation Example"
-- text: "Expert surgeons will intuitively navigate complex anatomical structures"
-  example_title: "Naturalization Example"
+  - text: "Students will observe and replicate the proper hand positioning during violin lessons"
+    example_title: "Imitation Example"
+  - text: "Learners will perform the CPR procedure following the training manual guidelines"
+    example_title: "Manipulation Example"
+  - text: "Nurses will accurately draw 5mL of medication into a syringe with 0.1mL precision"
+    example_title: "Precision Example"
+  - text: "Physical therapists will coordinate breathing patterns with stride rhythm"
+    example_title: "Articulation Example"
+  - text: "Expert surgeons will intuitively navigate complex anatomical structures"
+    example_title: "Naturalization Example"
+pipeline_tag: text-classification
 ---
 
 # Dave's Psychomotor Taxonomy Classifier
@@ -43,18 +41,19 @@ This model classifies educational learning objectives according to **R.H. Dave's
 - **Level 3: Articulation** - Coordinating multiple skills and adapting
 - **Level 4: Naturalization** - Automated, unconscious mastery
 
+## Model Details
+
+- **Model Type**: BERT-based sequence classification
+- **Base Model**: `bert-base-uncased`
+- **Fine-tuned on**: Custom dataset of psychomotor learning objectives
+- **Language**: English
+- **License**: Apache 2.0
+
 ## Training Data
 
 - **Dataset Size**: 298 learning objectives
 - **Balance**: ~60 examples per level
 - **Domains**: Medical/Healthcare, Sports, Performing Arts, Skilled Trades, Technology, Culinary Arts, Manufacturing, Emergency Services, Laboratory Sciences, Fine Arts
 
-## Model Performance
-
-- **Test Accuracy**: {overall_acc:.2%} (update after evaluation)
-- **Model Type**: BERT-base-uncased fine-tuned
-- **Training Epochs**: 5
-- **Batch Size**: 16
-
 ## Usage