Update README.md

README.md

@@ -1,16 +1,23 @@
 ---
 library_name: transformers
-base_model: deberta-v3-xsmall-readability-pretrain
+base_model:
+- microsoft/deberta-v3-xsmall
 tags:
 - generated_from_trainer
 model-index:
 - name: deberta-v3-xsmall-readability
   results: []
+license: mit
+datasets:
+- agentlans/readability
+language:
+- en
+pipeline_tag: text-classification
 ---
 
 # English Text Readability Prediction
 
-This model card describes a fine-tuned DeBERTa-v3-xsmall model for predicting the readability level of English texts.
+This is a fine-tuned DeBERTa-v3-xsmall model for predicting the readability level of English texts.
 
 Suitable for:
 - Assessing educational material complexity
@@ -57,7 +64,7 @@ text = ["One day, Tim's teddy bear was sad. Tim did not know why his teddy bear
         "A few years back, I decided it was time for me to take a break from my mundane routine and embark on an adventure.",
         "We also experimentally verify that simply scaling the pulse energy by 3/2 between linearly and circularly polarized pumping closely reproduces the soliton and dispersive wave dynamics."]
 result = readability(text)
-result
+[round(x, 1) for x in result] # Estimated reading grades [2.9, 9.8, 21.9]
 ```
 
 <details>
@@ -102,4 +109,4 @@ On the evaluation set:
 
 - The model should not be the sole determinant for content suitability decisions
   - The writer or publisher should also consider the content, context, and reader expectations
-- Potential social or societal biases due to the training data sources
+- Potential social or societal biases due to the training data sources