Update README.md

README.md

@@ -14,12 +14,10 @@ model-index:
   results: []
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-<!-- 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. -->
-
 # bert-large-cased-lora-finetuned-ner-EMBO-SourceData
 
-This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the source_data dataset.
+This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased).
+
 It achieves the following results on the evaluation set:
 - Loss: 0.1282
 - Precision: 0.7999
@@ -29,15 +27,25 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Token%20Classification/Monolingual/EMBO-SourceData%20with%20LoRA/NER%20Project%20Using%20EMBO-SourceData%20with%20LoRA.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://huggingface.co/datasets/EMBO/BLURB
+
+**Token Distribution**
+![Token Distribution](https://raw.githubusercontent.com/DunnBC22/NLP_Projects/main/Token%20Classification/Monolingual/EMBO-SourceData%20with%20LoRA/Images/Class%20Distribution.png)
+
+**Token Distribution After Removing 'O' Tokens**
+![Token Distribution After Removing 'O' Tokens](https://raw.githubusercontent.com/DunnBC22/NLP_Projects/main/Token%20Classification/Monolingual/EMBO-SourceData%20with%20LoRA/Images/Class%20Distribution%20After%20Removing%20Other%20Token.png)
+
+**Histogram of Tokenized Input Lengths**
+
+![](https://raw.githubusercontent.com/DunnBC22/NLP_Projects/main/Token%20Classification/Monolingual/EMBO-SourceData%20with%20LoRA/Images/Histogram%20of%20Encoded%20Token%20Input%20Lengths.png)
 
 ## Training procedure