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@@ -53,7 +53,7 @@ This pretraining data will not be opened to public due to Twitter policy.
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  ## Model
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  | Model name | Architecture | Size of training data | Size of validation data |
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  |-----------------------------------|-----------------|----------------------------|-------------------------|
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- | `ijebertweet-codemixed-bert-base` | BERT | 2.24 GB of text | 249 MB of text |
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  ## Evaluation Results
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  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:
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  ### Load model and tokenizer
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  ```python
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  from transformers import AutoTokenizer, AutoModel
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- tokenizer = AutoTokenizer.from_pretrained("fathan/ijebert-codemixed-bert-base")
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- model = AutoModel.from_pretrained("fathan/ijebert-codemixed-bert-base")
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  ```
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  ### Masked language model
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  ```python
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  from transformers import pipeline
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- pretrained_model = "fathan/ijebert-codemixed-bert-base"
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  fill_mask = pipeline(
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  "fill-mask",
 
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  ## Model
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  | Model name | Architecture | Size of training data | Size of validation data |
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  |-----------------------------------|-----------------|----------------------------|-------------------------|
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+ | `indojave-codemixed-bert-base` | BERT | 2.24 GB of text | 249 MB of text |
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  ## Evaluation Results
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  We train the data with 3 epochs and total steps of 296K for 12 days.
 
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  ### Load model and tokenizer
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  ```python
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  from transformers import AutoTokenizer, AutoModel
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+ tokenizer = AutoTokenizer.from_pretrained("fathan/indojave-codemixed-bert-base")
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+ model = AutoModel.from_pretrained("fathan/indojave-codemixed-bert-base")
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  ```
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  ### Masked language model
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  ```python
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  from transformers import pipeline
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+ pretrained_model = "fathan/indojave-codemixed-bert-base"
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  fill_mask = pipeline(
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  "fill-mask",