Update README.md

README.md

@@ -45,13 +45,13 @@ Thus it is useful for Natural Language Inference and related tasks such as Zero-
 - **Model type:** Transformer Encoder
 - **Language(s) (NLP):** Fine-tuned for Myanmar (Burmese) and English
 - **License:** MIT
-- **Finetuned from model:** mDeBERTa v3 base [https://huggingface.co/microsoft/mdeberta-v3-base]
-- **Paper :** For the foundation model mDeBERTa v3, please refer to the paper [https://arxiv.org/abs/2111.09543]
+- **Finetuned from model:** mDeBERTa v3 base https://huggingface.co/microsoft/mdeberta-v3-base
+- **Paper :** For the foundation model mDeBERTa v3, please refer to the paper https://arxiv.org/abs/2111.09543
 - **Demo :** A demo of Zero-shot Text Classification in Myanmar can be found on this page.
 
 ## Bias, Risks, and Limitations
 
-Please refer to the papers for original foundation model: DeBERTa [https://arxiv.org/abs/2006.03654] and 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
@@ -78,12 +78,12 @@ Fore more details on zero-shot classification, please refer to HuggingFace docum
 
 ## Training Details
 
-The model is fine-tuned on myXNLI dataset [https://huggingface.co/datasets/akhtet/myXNLI]. The English portion of myXNLI is from XNLI dataset.
+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 approach was inspired by 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
 
 The model was fine-tuned using this combined dataset for a single epoch.