Update README.md

README.md

@@ -14,23 +14,17 @@ model-index:
 
 # distilbert-base-uncased-finetuned-emotion
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2054
-- Accuracy: 0.931
-- F1: 0.9309
-
 ## Model description
 
-More information needed
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on `emotion` dataset. The dataset consists of 1658616 examples of text and emotion labels. The emotion labels are one of the following: 'joy', 'sadness', 'fear', 'anger', 'surprise'. The model was fine-tuned using the `Trainer` API from the `transformers` library on the `emotion` dataset.
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended to be used for emotion classification tasks. The model is trained on English text data and may not perform well on other languages. The model is trained on the `emotion` dataset and may not perform well on other emotion classification tasks.
 
 ## Training and evaluation data
 
-More information needed
+The model was trained on the `emotion` dataset. The dataset consists of 1658616 examples of text and emotion labels. The emotion labels are one of the following: 'joy', 'sadness', 'fear', 'anger', 'surprise'.
 
 ## Training procedure
 
@@ -52,6 +46,10 @@ The following hyperparameters were used during training:
 | 0.7763        | 1.0   | 250  | 0.2839          | 0.9145   | 0.9141 |
 | 0.2336        | 2.0   | 500  | 0.2054          | 0.931    | 0.9309 |
 
+It achieves the following results on the evaluation set:
+- Loss: 0.2054
+- Accuracy: 0.931
+- F1: 0.9309
 
 ### Framework versions