Update README.md

README.md

@@ -16,7 +16,7 @@ widget:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# IJEBERT: IndoBERTweet-base
+# Indojave: IndoBERTweet-base
 
 ## About
 This is a pre-trained masked language model for code-mixed Indonesian-Javanese-English tweets data.
@@ -53,7 +53,7 @@ This pretraining data will not be opened to public due to Twitter policy.
 ## Model
 | Model name                                | Architecture    | Size of training data      | Size of validation data |
 |-------------------------------------------|-----------------|----------------------------|-------------------------|
-| `ijebertweet-codemixed-indobertweet-base` | BERT            | 2.24 GB of text            | 249 MB of text          |  
+| `indojave-codemixed-indobertweet-base`    | BERT            | 2.24 GB of text            | 249 MB of text          |  
 
 ## Evaluation Results
 We train the data with 3 epochs and total steps of 296K for 4 days.
@@ -67,15 +67,15 @@ The following are the results obtained from the training:
 ### Load model and tokenizer
 ```python
 from transformers import AutoTokenizer, AutoModel
-tokenizer = AutoTokenizer.from_pretrained("fathan/ijebert-codemixed-indobertweet-base")
-model = AutoModel.from_pretrained("fathan/ijebert-codemixed-indobertweet-base")
+tokenizer = AutoTokenizer.from_pretrained("fathan/indojave-codemixed-indobertweet-base")
+model = AutoModel.from_pretrained("fathan/indojave-codemixed-indobertweet-base")
 
 ```
 ### Masked language model
 ```python
 from transformers import pipeline
 
-pretrained_model = "fathan/ijebert-codemixed-indobertweet-base"
+pretrained_model = "fathan/indojave-codemixed-indobertweet-base"
 
 fill_mask = pipeline(
     "fill-mask",