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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: indobenchmark/indobert-large-p1
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: indobert-large-p1-twitter-indonesia-sarcastic
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+ results: []
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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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+ # indobert-large-p1-twitter-indonesia-sarcastic
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+
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+ This model is a fine-tuned version of [indobenchmark/indobert-large-p1](https://huggingface.co/indobenchmark/indobert-large-p1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5739
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+ - Accuracy: 0.8619
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+ - F1: 0.7218
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+ - Precision: 0.7273
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+ - Recall: 0.7164
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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: 1e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 64
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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: cosine
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+ - num_epochs: 100.0
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+ - mixed_precision_training: Native AMP
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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 | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.5836 | 1.0 | 59 | 0.4153 | 0.8060 | 0.5738 | 0.6364 | 0.5224 |
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+ | 0.3766 | 2.0 | 118 | 0.3353 | 0.8433 | 0.5962 | 0.8378 | 0.4627 |
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+ | 0.2476 | 3.0 | 177 | 0.3114 | 0.8619 | 0.6942 | 0.7778 | 0.6269 |
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+ | 0.1356 | 4.0 | 236 | 0.3279 | 0.8694 | 0.7328 | 0.75 | 0.7164 |
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+ | 0.0536 | 5.0 | 295 | 0.4265 | 0.8582 | 0.7164 | 0.7164 | 0.7164 |
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+ | 0.0157 | 6.0 | 354 | 0.6448 | 0.8619 | 0.6667 | 0.8409 | 0.5522 |
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+ | 0.0076 | 7.0 | 413 | 0.5739 | 0.8619 | 0.7218 | 0.7273 | 0.7164 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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