Update README.md

README.md

@@ -3,13 +3,15 @@ license: cc-by-nc-sa-4.0
 base_model: microsoft/layoutlmv3-base
 tags:
 - generated_from_trainer
+- Document Layout
+- LayoutLMv3
 datasets:
 - funsd-layoutlmv3
 metrics:
-- precision
-- recall
 - f1
 - accuracy
+- recall
+- precision
 model-index:
 - name: layoutlmv3-base-fine_tuned-FUNSD_dataset
   results:
@@ -35,14 +37,14 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.8461904195887318
+language:
+- en
 ---
 
-<!-- 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. -->
-
 # layoutlmv3-base-fine_tuned-FUNSD_dataset
 
 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd-layoutlmv3 dataset.
+
 It achieves the following results on the evaluation set:
 - Loss: 0.2956
 - Precision: 0.8979
@@ -52,15 +54,15 @@ 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: 
 
 ## 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/nielsr/funsd-layoutlmv3
 
 ## Training procedure
 
@@ -77,7 +79,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+| Train Loss | Epoch | Step | Valid. Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
 | 0.2149        | 1.33  | 100  | 0.2402          | 0.7469    | 0.8212 | 0.7823 | 0.7758   |
 | 0.1466        | 2.67  | 200  | 0.1869          | 0.8161    | 0.8838 | 0.8486 | 0.8273   |
@@ -106,4 +108,4 @@ The following hyperparameters were used during training:
 - Transformers 4.33.2
 - Pytorch 2.0.1
 - Datasets 2.14.5
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3