Update README.md

README.md

@@ -4,6 +4,9 @@ tags:
 model-index:
 - name: 20231102-20_epochs_layoutlmv2-base-uncased_finetuned_docvqa
   results: []
+license: mit
+datasets:
+- zibajoon/20231109_layoutlm2_5k_20_epochs
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,15 +20,15 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This DocVQA model, built on the Layout LM v2 framework, represents an initial step in a series of experimental models aimed at document visual question answering. It's the "mini" version in a planned series, trained on a relatively small dataset of 1.2k samples (1,000 for training and 200 for testing) over 20 epochs. The training setup was modest, employing mixed precision (fp16), with manageable batch sizes and a focused approach to learning rate adjustment (warmup steps and weight decay). Notably, this model was trained without external reporting tools, emphasizing internal evaluation. As the first iteration in a progressive series that will later include medium (5k samples) and large (50k samples) models, this version serves as a foundational experiment, setting the stage for more extensive and complex models in the future.
 
 ## Intended uses & limitations
 
-More information needed
+Experimental Only
 
 ## Training and evaluation data
 
-More information needed
+Based on the sample 1.2 dataset released by DocVQA
 
 ## Training procedure
 
@@ -58,4 +61,4 @@ The following hyperparameters were used during training:
 - Transformers 4.34.1
 - Pytorch 2.0.1+cu118
 - Datasets 2.10.1
-- Tokenizers 0.14.1
+- Tokenizers 0.14.1