Update README.md

README.md

@@ -227,7 +227,7 @@ A summary of the [infamous navy seals copypasta](https://knowyourmeme.com/memes/
 
 A fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the `kmfoda/booksum` dataset:
 
-- 20+ epochs of fine-tuning from the base model on V100/A100 GPUs
+- 30+ epochs of fine-tuning from the base model on V100/A100 GPUs
 - all training used 16384 token input / 1024 max output
 
 Read the paper by Guo et al. here: [LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://arxiv.org/pdf/2112.07916.pdf) 
@@ -262,9 +262,9 @@ Pass [other parameters related to beam search textgen](https://huggingface.co/bl
 
 ## Training and evaluation data
 
-`kmfoda/booksum` dataset on HuggingFace - read [the original paper here](https://arxiv.org/abs/2105.08209). Summaries longer than 1024 LongT5 tokens were filtered out with the intent of preventing the model from learning to generate "partial" summaries.
+`kmfoda/booksum` dataset on HuggingFace - read [the original paper here](https://arxiv.org/abs/2105.08209). Summaries longer than 1024 LongT5 tokens were filtered out to prevent the model from learning to generate "partial" summaries.
 
-_NOTE: 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._
+_NOTE: 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 10+ epochs._
 
 ## Training procedure
 
@@ -274,9 +274,9 @@ _NOTE: early checkpoints of this model were trained on a "smaller" subsection of
 
 ### Training hyperparameters
 
-The following hyperparameters were used during the **final** training round\*:
+The following hyperparameters were used during the **most recent** training round\*:
 
-- learning_rate: 0.001
+- learning_rate: 0.0006
 - train_batch_size: 1
 - eval_batch_size: 1
 - seed: 42
@@ -289,7 +289,7 @@ The following hyperparameters were used during the **final** training round\*:
 - num_epochs: 2
 
 
-\*_Prior training sessions used roughly similar parameters; multiple sessions were required as this takes eons to train_
+\*_Prior training sessions used roughly similar parameters; multiple sessions were required as this takes aeons to train_
 
 ### Training results