v0.3 - add data to train.csv

README.md

@@ -10,8 +10,8 @@ dataset_info:
     - name: label, text
   splits:
     - name: train
-      num_bytes: 270
-      num_examples: 10
+      num_bytes: 837
+      num_examples: 31
     - name: validation
       num_bytes: 75
       num_examples: 3
@@ -20,7 +20,7 @@ dataset_info:
       num_examples: 3
 ---
 
-# Dataset Card for sentiment-test-dataset
+# Dataset Card for test-dataset
 
 ## Dataset Details
 
@@ -31,7 +31,7 @@ A collection of labeled examples for training and evaluating machine learning mo
 - **Curated by:** Ruihao
 - **Language(s):** en
 - **License:** cc-by-4.0
-- **Size of the dataset:** 10 train, 3 validation, 3 test
+- **Size of the dataset:** 31 train, 3 validation, 3 test
 
 ## Dataset Structure
 
@@ -47,7 +47,7 @@ The dataset contains the following fields: label, text.
 
 | Split | Size |
 |-------|------|
-| train | 10 |
+| train | 31 |
 | validation | 3 |
 | test | 3 |
 

train.csv

@@ -9,3 +9,24 @@ text,label
 "Okay movie",neutral
 "It was alright",neutral
 "Spectacular cinematography",positive
+"Outstanding directing and storytelling",positive
+"Brilliant actors and great dialogue",positive
+"One of the best movies I've seen",positive
+"Absolutely recommend this film",positive
+"Such a waste of time",negative
+"Boring and predictable",negative
+"Terrible script and poor execution",negative
+"Not worth watching",negative
+"Could have been better",neutral
+"Nothing special about it",neutral
+"It has its moments",neutral
+"Decent but forgettable",neutral
+"Impressive visual effects",positive
+"Great soundtrack and pacing",positive
+"Emotionally powerful performance",positive
+"Completely disappointed",negative
+"Awful from start to finish",negative
+"Painful to watch",negative
+"Average film overall",neutral
+"Some good parts, some bad",neutral
+"Not bad, not great",neutral