Update README.md

README.md

@@ -2,45 +2,44 @@
 tags:
 - generated_from_keras_callback
 model-index:
-- name: twitter-roberta-base-emotion-multi
+- name: twitter-roberta-base-emotion-multilabel-latest
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information Keras had access to. You should
 probably proofread and complete it, then remove this comment. -->
 
-# twitter-roberta-base-emotion-multi
+# twitter-roberta-base-emotion-multilabel-latest
 
-This model was trained from scratch on an unknown dataset.
-It achieves the following results on the evaluation set:
+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 
+[`SemEval 2018 - Task 1 Affect in Tweets`](https://aclanthology.org/S18-1001/) `(subtask: E-c / multilabel classification)`.
 
 
-## Model description
 
-More information needed
+## Performance
 
-## Intended uses & limitations
+Following metrics are achieved on the test split:
 
-More information needed
+- F1 (micro): 0.7218
+- F1 (macro): 0.5746  
+- Jaccard Index (samples): 0.6073: 
 
-## Training and evaluation data
+### Usage
+#### 1. [tweetnlp][https://pypi.org/project/tweetnlp/]
+Install tweetnlp via pip.
+```shell
+pip install tweetnlp
+```
+Load the model in python.
+```python
+import tweetnlp
+....
+```
+#### 2. pipeline
 
-More information needed
 
-## Training procedure
+### Reference 
 
-### Training hyperparameters
+ ....
 
-The following hyperparameters were used during training:
-- optimizer: None
-- training_precision: float32
 
-### Training results
-
-
-
-### Framework versions
-
-- Transformers 4.26.1
-- TensorFlow 2.10.0
-- Tokenizers 0.13.2