Update README.md

README.md

@@ -10,14 +10,30 @@ metrics:
 library_name: transformers
 pipeline_tag: fill-mask
 ---
+
 ### SRDberta
 
-This is a BERT model trained for Masked Language Modeling for Higlish Data.
+This is a BERT model trained for Masked Language Modeling for Hinglish Data.
 
 Hinglish is a term used to describe the hybrid language spoken in India, which combines elements of Hindi and English. It is commonly used in informal conversations and in media such as Bollywood films
 
+### Dataset
+Hinglish-Top [Dataset](https://huggingface.co/datasets/WillHeld/hinglish_top) columns
+- en_query
+- cs_query
+- en_parse 
+- cs_parse 
+- domain 
+
+### Training
+|Epochs|Train Loss|
+|:------:|:----------:|
+|4th   |   0.251 |
+
+The model was trained only for 4 epochs due to the GPU limitations. The model will give far better results with 10 epochs
+
 ### Inference 
-```
+```python
 from transformers import AutoTokenizer, AutoModelForMaskedLM, pipeline
 
 tokenizer = AutoTokenizer.from_pretrained("SRDdev/SRDBerta")
@@ -26,7 +42,7 @@ model = AutoModelForMaskedLM.from_pretrained("SRDdev/SRDBerta")
 
 fill = pipeline('fill-mask', model='SRDberta', tokenizer='SRDberta')
 ```
-```
+```python
 fill_mask = fill.tokenizer.mask_token
 fill(f'Aap {fill_mask} ho?')
 ```
@@ -34,6 +50,10 @@ fill(f'Aap {fill_mask} ho?')
 ### Citation
 Author: @[SRDdev](https://huggingface.co/SRDdev)
 ```
+Name : Shreyas Dixit
 framework : Pytorch
 Year: Jan 2023
-```
+Pipeline : fill-mask
+Github : https://github.com/SRDdev
+LinkedIn : https://www.linkedin.com/in/srddev/ 
+```