Update README.md

README.md

@@ -7,11 +7,13 @@ metrics:
 model-index:
 - name: codet5-small-Generate_Docstrings_for_Python-Condensed
   results: []
+datasets:
+- calum/the-stack-smol-python-docstrings
+language:
+- en
+pipeline_tag: text2text-generation
 ---
 
-<!-- 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. -->
-
 # codet5-small-Generate_Docstrings_for_Python-Condensed
 
 This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the None dataset.
@@ -25,15 +27,19 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This model is trained to predict the docstring (the output) for a function (the input).
+
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Generate%20Docstrings/Smol%20Dataset/Code_T5_Project-Small%20Checkpoint.ipynb
+
+For this model, I trimmed some of the longer samples to quicken the pace of training on consumer hardware.
 
 ## 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: calum/the-stack-smol-python-docstrings (from HuggingFace Datasets; https://huggingface.co/datasets/calum/the-stack-smol-python-docstrings)
 
 ## Training procedure
 
@@ -63,4 +69,4 @@ The following hyperparameters were used during training:
 - Transformers 4.26.1
 - Pytorch 1.12.1
 - Datasets 2.9.0
-- Tokenizers 0.12.1
+- Tokenizers 0.12.1