Update README.md

README.md

@@ -5,34 +5,38 @@ tags:
 metrics:
 - accuracy
 model-index:
-- name: deberta-v3-large-emotion-lr7e-6-gas1-ls0.1
+- name: deberta-v3-large
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# deberta-v3-large-sentiment
 
-# deberta-v3-large-emotion-lr7e-6-gas1-ls0.1
-
-This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.8311
-- Accuracy: 0.8235
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an [tweet_eval](https://huggingface.co/datasets/tweet_eval)  dataset.
 
 ## Model description
 
-More information needed
+Test set results:
+
+| Model                      | Emotion       | Hate          | Irony         | Offensive     | Sentiment     | 
+| -------------              | ------------- | ------------- | ------------- | ------------- | ------------- | 
+| deberta-v3-large           | **86.3**      | **61.3**      | **87.1**      | **86.4**      | **73.9**      | 
+| BERTweet                   | 79.3          | -             | 82.1          | 79.5          | 73.4          | 
+| RoB-RT                     | 79.5          | 52.3          | 61.7          | 80.5          | 69.3          | 
+
+[source:papers_with_code](https://paperswithcode.com/sota/sentiment-analysis-on-tweeteval)
+
 
 ## Intended uses & limitations
 
-More information needed
+Classifying attributes of interest on tweeter like data. 
 
 ## Training and evaluation data
 
-More information needed
+[tweet_eval](https://huggingface.co/datasets/tweet_eval)  dataset.
 
 ## Training procedure
 
+Fine tuned and evaluated with [run_glue.py]()
 ### Training hyperparameters
 
 The following hyperparameters were used during training: