Update README.md

README.md

@@ -51,7 +51,7 @@ Thus it is useful for Natural Language Inference and related tasks such as Zero-
 
 ## Bias, Risks, and Limitations
 
-Please consult the papers for original foundation model DeBERTaV3 [https://arxiv.org/abs/2111.09543].
+Please refer to the papers for original foundation model: DeBERTa [https://arxiv.org/abs/2006.03654] and DeBERTaV3 [https://arxiv.org/abs/2111.09543].
 <!-- Any limitations with myXNLI ? -->
 
 ## How to Get Started with the Model
@@ -62,53 +62,24 @@ Use the code below to get started with the model.
 
 ## Training Details
 
-The model is fine-tuned on myXNLI dataset https://huggingface.co/datasets/akhtet/myXNLI
+The model is fine-tuned on myXNLI dataset [https://huggingface.co/datasets/akhtet/myXNLI]. The English portion of myXNLI is from XNLI dataset.
 
 From this dataset, 4 different copies training data from myXNLI were concatenated, each with sentence pairs in en-en, en-my, my-en and my-my combinations.
 
 Training on cross-matched language data as above improved the NLI accuracy over training separately in each language. 
-This was inspired by the approach from another model [https://huggingface.co/joeddav/xlm-roberta-large-xnli]
+This approach was inspired by another model [https://huggingface.co/joeddav/xlm-roberta-large-xnli]
 
-### Training Procedure 
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+The model was fine-tuned using this combined dataset for a single epoch. 
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Data Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
+This model has been evaluted on myXNLI testset for Myanmar accuracy. We also provide the accuracy for English using XNLI testset.
 
-https://www.bbc.com/burmese/articles/cmj15enzk2go
-https://my.wikipedia.org/wiki/%E1%80%A1%E1%80%B1%E1%80%AC%E1%80%84%E1%80%BA%E1%80%9C%E1%80%A1%E1%80%94%E1%80%BA%E1%80%86%E1%80%94%E1%80%BA%E1%80%B8
+| Model | Myanmar accuracy | English accuracy | 
+| ----- | ----- | ----- |
+| mDeBERTa-v3-base-myXNLI | 88.02 | 80.99 | 
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
@@ -118,4 +89,4 @@ https://my.wikipedia.org/wiki/%E1%80%A1%E1%80%B1%E1%80%AC%E1%80%84%E1%80%BA%E1%8
 
 ## Model Card Contact
 
-[More Information Needed]
+Aung Kyaw Htet