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README.md
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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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## 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/
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model = AutoModel.from_pretrained("fathan/
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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/
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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",
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