Update README.md

README.md

@@ -5,16 +5,16 @@ tags:
 metrics:
 - rouge
 model-index:
-- name: flan-t5-base-text_summarization_data_3_epochs
+- name: flan-t5-base-text_summarization_data_6_epochs
   results: []
+language:
+- en
+pipeline_tag: summarization
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# flan-t5-base-text_summarization_data_6_epochs
 
-# flan-t5-base-text_summarization_data_3_epochs
-
-This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
+This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base).
 It achieves the following results on the evaluation set:
 - Loss: 1.6783
 - Rouge1: 43.5994
@@ -25,15 +25,17 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is a text summarization model.
+
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Text%20Summarization/Text-Summarized%20Data%20-%20Comparison/Flan-T5%20-%20Text%20Summarization%20-%206%20Epochs.ipynb
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended to demonstrate my ability to solve a complex problem using technology.
 
 ## Training and evaluation data
 
-More information needed
+Dataset Source: https://www.kaggle.com/datasets/cuitengfeui/textsummarization-data
 
 ## Training procedure
 
@@ -65,4 +67,4 @@ The following hyperparameters were used during training:
 - Transformers 4.26.1
 - Pytorch 1.13.1+cu116
 - Datasets 2.10.1
-- Tokenizers 0.13.2
+- Tokenizers 0.13.2