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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: indolem/indobert-base-uncased
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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-base-uncased-reddit-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-base-uncased-reddit-indonesia-sarcastic
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+
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+ This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6153
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+ - Accuracy: 0.7817
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+ - F1: 0.5523
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+ - Precision: 0.5672
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+ - Recall: 0.5382
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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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+ | 0.5121 | 1.0 | 309 | 0.4942 | 0.7378 | 0.4774 | 0.4761 | 0.4788 |
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+ | 0.4513 | 2.0 | 618 | 0.4422 | 0.7952 | 0.4956 | 0.6455 | 0.4023 |
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+ | 0.4078 | 3.0 | 927 | 0.4771 | 0.7980 | 0.4075 | 0.7656 | 0.2776 |
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+ | 0.3686 | 4.0 | 1236 | 0.4755 | 0.8051 | 0.4898 | 0.7097 | 0.3739 |
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+ | 0.3358 | 5.0 | 1545 | 0.4864 | 0.7753 | 0.5768 | 0.5455 | 0.6119 |
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+ | 0.299 | 6.0 | 1854 | 0.5038 | 0.7633 | 0.5729 | 0.5221 | 0.6346 |
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+ | 0.2602 | 7.0 | 2163 | 0.5242 | 0.7888 | 0.5387 | 0.5939 | 0.4929 |
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+ | 0.2184 | 8.0 | 2472 | 0.6153 | 0.7817 | 0.5523 | 0.5672 | 0.5382 |
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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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