Update README.md

README.md

@@ -6,6 +6,14 @@ tags:
 model-index:
 - name: FYP_qa_final
   results: []
+datasets:
+- rajpurkar/squad_v2
+- mrqa
+- UCLNLP/adversarial_qa
+- mbartolo/synQA
+language:
+- en
+pipeline_tag: question-answering
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -13,13 +21,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # FYP_qa_final
 
-This model is a fine-tuned version of [kxx-kkk/FYP_sq2_mrqa_adqa_synqa](https://huggingface.co/kxx-kkk/FYP_sq2_mrqa_adqa_synqa) on an unknown dataset.
+This model is a fine-tuned version of [deepset/deberta-v3-base-squad2](https://huggingface.co/deepset/deberta-v3-base-squad2) on an [MRQA](https://huggingface.co/datasets/mrqa) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 2.7493
 
 ## Model description
 
-More information needed
+This model is trained for performing extractive question-answering tasks for academic essays. 
 
 ## Intended uses & limitations
 
@@ -27,7 +35,11 @@ More information needed
 
 ## Training and evaluation data
 
-More information needed
+The dataset used for training is listed below according to training sequences:
+1. [MRQA(train split)](https://huggingface.co/datasets/mrqa)
+2. [UCLNLP/adversarial_qa](https://huggingface.co/datasets/UCLNLP/adversarial_qa)
+3. [mbartolo/synQA](https://huggingface.co/datasets/mbartolo/synQA)
+4. [MRQA(test split)](https://huggingface.co/datasets/mrqa)
 
 ## Training procedure
 
@@ -60,4 +72,4 @@ The following hyperparameters were used during training:
 - Transformers 4.39.3
 - Pytorch 2.2.1+cu121
 - Datasets 2.18.0
-- Tokenizers 0.15.2
+- Tokenizers 0.15.2