Update README.md

README.md

@@ -16,10 +16,10 @@ 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. -->
 
-# Code-mixed IJEBERT
+# IJEBERTweet: BERT-base
 
 ## About
-Code-mixed IJEBERT is a pre-trained masked language model for code-mixed Indonesian-Javanese-English tweets data.
+This is a pre-trained masked language model for code-mixed Indonesian-Javanese-English tweets data.
 This model is trained based on [BERT](https://arxiv.org/abs/1810.04805) model utilizing 
 Hugging Face's [Transformers]((https://huggingface.co/transformers)) library.
 
@@ -51,9 +51,9 @@ Finally, we have 28,121,693 sentences for the training process.
 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 |
-|----------------------|-----------------|----------------------------|-------------------------|
-| `code-mixed-ijebert` | BERT            | 2.24 GB of text            | 249 MB of text          |  
+| Model name                        | Architecture    | Size of training data      | Size of validation data |
+|-----------------------------------|-----------------|----------------------------|-------------------------|
+| `ijebertweet-codemixed-bert-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 12 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/code-mixed-ijebert")
-model = AutoModel.from_pretrained("fathan/code-mixed-ijebert")
+tokenizer = AutoTokenizer.from_pretrained("fathan/ijebertweet-codemixed-bert-base")
+model = AutoModel.from_pretrained("fathan/ijebertweet-codemixed-bert-base")
 
 ```
 ### Masked language model
 ```python
 from transformers import pipeline
 
-pretrained_model = "fathan/code-mixed-ijebert"
+pretrained_model = "fathan/ijebertweet-codemixed-bert-base"
 
 fill_mask = pipeline(
     "fill-mask",