Update README.md

README.md

@@ -193,20 +193,7 @@ Exploring how well long-document models trained on "lay summaries" of scientific
 
 ## Model description
 
-This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the `pszemraj/scientific_lay_summarisation-plos-norm` dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.6778
-- Rouge1: 49.1475
-- Rouge2: 18.9281
-- Rougel: 26.9893
-- Rougelsum: 45.0973
-- Gen Len: 399.4125
-
-
-## Intended uses & limitations
-
-- Ability to generalize outside of the dataset domain (pubmed/bioscience type papers) has to be evaluated.
-
+This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the `pszemraj/scientific_lay_summarisation-plos-norm` dataset for two epochs.
 
 ## Usage 
 
@@ -226,8 +213,24 @@ summary = summarizer.summarize_string(text)
 print(summary)
 ```
 
+## Intended uses & limitations
+
+- Ability to generalize outside of the dataset domain (pubmed/bioscience type papers) has to be evaluated.
+
+
 ## Training procedure
 
+
+### Eval results
+
+It achieves the following results on the evaluation set:
+- Loss: 1.6778
+- Rouge1: 49.1475
+- Rouge2: 18.9281
+- Rougel: 26.9893
+- Rougelsum: 45.0973
+- Gen Len: 399.4125
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: