Update README.md

README.md

@@ -14,7 +14,7 @@ probably proofread and complete it, then remove this comment. -->
 
 # twitter-roberta-base-emotion-multilabel-latest
 
-This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2021-124m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m) on the 
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2022-154m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m) on the 
 [`SemEval 2018 - Task 1 Affect in Tweets`](https://aclanthology.org/S18-1001/) `(subtask: E-c / multilabel classification)`.
 
 
@@ -23,9 +23,9 @@ This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2021-124m
 
 Following metrics are achieved on the test split:
 
-- F1 (micro): 0.7218
-- F1 (macro): 0.5746  
-- Jaccard Index (samples): 0.6073: 
+- F1 (micro): 0.7169
+- F1 (macro): 0.5464  
+- Jaccard Index (samples): 0.5970: 
 
 ### Usage
 #### 1. [tweetnlp](https://pypi.org/project/tweetnlp/)
@@ -39,9 +39,9 @@ import tweetnlp
 
 model = tweetnlp.load_model('topic_classification', model_name='cardiffnlp/twitter-roberta-base-emotion-multilabel-latest')
 
-model.predict("I am so happy and sad at the same time")
+model.predict("I bet everything will work out in the end :)")
 
->> {'label': ['joy', 'sadness']}
+>> {'label': ['joy', 'optimism']}
 
 ```
 #### 2. pipeline
@@ -56,18 +56,17 @@ pipe = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-em
 
 pipe("I am so happy and sad at the same time")
 
->> [[{'label': 'anger', 'score': 0.0059011634439229965},
-  {'label': 'anticipation', 'score': 0.024502484127879143},
-  {'label': 'disgust', 'score': 0.016748998314142227},
-  {'label': 'fear', 'score': 0.20184014737606049},
-  {'label': 'joy', 'score': 0.9260002970695496},
-  {'label': 'love', 'score': 0.13167349994182587},
-  {'label': 'optimism', 'score': 0.32711178064346313},
-  {'label': 'pessimism', 'score': 0.08952841907739639},
-  {'label': 'sadness', 'score': 0.8542942404747009},
-  {'label': 'surprise', 'score': 0.059213291853666306},
-  {'label': 'trust', 'score': 0.01618659868836403}]]
-
+>> [[{'label': 'anger', 'score': 0.018903767690062523},
+  {'label': 'anticipation', 'score': 0.28172484040260315},
+  {'label': 'disgust', 'score': 0.011607927270233631},
+  {'label': 'fear', 'score': 0.036411102861166},
+  {'label': 'joy', 'score': 0.8812029361724854},
+  {'label': 'love', 'score': 0.09591569006443024},
+  {'label': 'optimism', 'score': 0.9810988306999207},
+  {'label': 'pessimism', 'score': 0.016823478043079376},
+  {'label': 'sadness', 'score': 0.01889917254447937},
+  {'label': 'surprise', 'score': 0.02702752873301506},
+  {'label': 'trust', 'score': 0.4155798852443695}]]
 ```