antypasd commited on
Commit
723a368
1 Parent(s): 6b727ec

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +3 -11
README.md CHANGED
@@ -6,17 +6,9 @@ model-index:
6
  results: []
7
  ---
8
 
9
- ---
10
- tags:
11
- - generated_from_keras_callback
12
- model-index:
13
- - name: XLM-T-Sent-Politics
14
- results: []
15
- ---
16
-
17
- # XLM-T-Sent-Politics
18
 
19
- This is an "extension" of the `twitter-roberta-base-sentiment-latest` model ([model](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest), further finetuned with original Twitter data posted in English about the 10th anniversary of the 2010 Haiti Earthquake.
20
 
21
  - Reference Paper: [Sentiment analysis (SA) (supervised and unsupervised classification) of original Twitter data posted in English about the 10th anniversary of the 2010 Haiti Earthquake](https://data.ncl.ac.uk/articles/dataset/Sentiment_analysis_SA_supervised_and_unsupervised_classification_of_original_Twitter_data_posted_in_English_about_the_10th_anniversary_of_the_2010_Haiti_Earthquake/19688040/1).
22
 
@@ -56,7 +48,7 @@ prediction = np.argmax(scores)
56
  # prediction = np.argmax(scores)
57
 
58
  # Print label
59
- print(text, class_mapping[prediction])
60
 
61
  ```
62
 
 
6
  results: []
7
  ---
8
 
9
+ # twitter-roberta-base-sentiment-earthquake
 
 
 
 
 
 
 
 
10
 
11
+ This is an "extension" of the `twitter-roberta-base-sentiment-latest` [model](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest), further finetuned with original Twitter data posted in English about the 10th anniversary of the 2010 Haiti Earthquake.
12
 
13
  - Reference Paper: [Sentiment analysis (SA) (supervised and unsupervised classification) of original Twitter data posted in English about the 10th anniversary of the 2010 Haiti Earthquake](https://data.ncl.ac.uk/articles/dataset/Sentiment_analysis_SA_supervised_and_unsupervised_classification_of_original_Twitter_data_posted_in_English_about_the_10th_anniversary_of_the_2010_Haiti_Earthquake/19688040/1).
14
 
 
48
  # prediction = np.argmax(scores)
49
 
50
  # Print label
51
+ print(class_mapping[prediction])
52
 
53
  ```
54