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update model card README.md

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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - indonlu
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bert-base-indonesian-1.5G-finetuned-wnli
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: indonlu
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+ type: indonlu
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+ args: smsa
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9373015873015873
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert-base-indonesian-1.5G-finetuned-wnli
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+
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+ This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on the indonlu dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3390
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+ - Accuracy: 0.9373
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2864 | 1.0 | 688 | 0.2154 | 0.9286 |
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+ | 0.1648 | 2.0 | 1376 | 0.2238 | 0.9357 |
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+ | 0.0759 | 3.0 | 2064 | 0.3351 | 0.9365 |
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+ | 0.044 | 4.0 | 2752 | 0.3390 | 0.9373 |
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+ | 0.0308 | 5.0 | 3440 | 0.4346 | 0.9365 |
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+ | 0.0113 | 6.0 | 4128 | 0.4708 | 0.9365 |
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+ | 0.006 | 7.0 | 4816 | 0.5533 | 0.9325 |
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+ | 0.0047 | 8.0 | 5504 | 0.5888 | 0.9310 |
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+ | 0.0001 | 9.0 | 6192 | 0.5961 | 0.9333 |
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+ | 0.0 | 10.0 | 6880 | 0.5992 | 0.9357 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.14.1
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.16.1
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+ - Tokenizers 0.10.3