embellish das README

README.md

@@ -64,33 +64,35 @@ inference:
     
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-# long-t5-tglobal-base-16384-booksum-V7
+# long-t5-tglobal-base-16384-booksum
 
-- summarize long text and get a sparknotes-esque summary!
+- summarize long text and get a SparkNotes-esque summary of arbitrary topics!
 - generalizes fairly well to academic & narrative text. 
 
 ## Cheeky Proof-of-Concept
 
-A summary of the [famous navy seals copypasta](https://knowyourmeme.com/memes/navy-seal-copypasta):
+A summary of the [infamous navy seals copypasta](https://knowyourmeme.com/memes/navy-seal-copypasta):
 
 > The narrator tells the audience that he can kill anyone anywhere in the world with his bare hands, and he has access to all of the United States military's weapons.
 
 
 ## 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 `kmfoda/booksum` dataset:
+A fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the `kmfoda/booksum` dataset:
+
 - between different checkpoints, about 20 epochs in total
 - all training was done at 16384 token input / 1024 max output
 - early checkpoints of this model were trained on a "smaller" subsection of the dataset as it was filtered for summaries of 1024 **characters**. This was subsequently caught and adjusted to **1024** tokens, and then trained further for at least five epochs. 
 
 ## Intended uses & limitations
 
-- At time of writing, the model is not _fully converged_ despite training for 20+ epochs. This checkpoint is servicable enough (see examples).
+- At time of writing, the model is not _fully converged_ despite training for 20+ epochs. This checkpoint is serviceable enough (see examples).
 - I plan to update this page with newer checkpoints and post some metrics over time.
+- Compare performance to [LED-base](https://huggingface.co/pszemraj/led-base-book-summary) trained on the same dataset.
 
 ## Training and evaluation data
 
-More information needed
+`kmfoda/booksum` dataset. Summaries longer than 1024 LongT5 tokens were filtered out to prevent the model from learning to generate "partial" summaries.
 
 ## Training procedure