Update README.md

README.md

@@ -4,11 +4,18 @@ license: apache-2.0
 base_model: distilbert/distilroberta-base
 tags:
 - generated_from_trainer
+- sentiment_analysis
 model-index:
 - name: go-emotions-plus-other-datasets-fine-tuned-distilroberta
   results: []
 datasets:
 - google-research-datasets/go_emotions
+language:
+- en
+metrics:
+- f1
+- precision
+- recall
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,7 +23,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # go-emotions-plus-other-datasets-fine-tuned-distilroberta
 
-This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset.
+This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the these datasets:
+   - [GoEmotions](https://github.com/google-research/google-research/tree/master/goemotions)
+   - [sem_eval_2018_task_1 (English)](https://huggingface.co/datasets/SemEvalWorkshop/sem_eval_2018_task_1)
+   - [Emotion Detection from Text - Pashupati Gupta](https://www.kaggle.com/datasets/pashupatigupta/emotion-detection-from-text/data)
+   - [Emotions dataset for NLP - praveengovi](https://www.kaggle.com/datasets/praveengovi/emotions-dataset-for-nlp/data)
+
+
 It achieves the following results on the evaluation set:
 - Loss: 0.0719
 - Micro Precision: 0.7358