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umn-cyber/indobert-hoax-detection

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  1. README.md +14 -15
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  library_name: transformers
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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:
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # results
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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: 0.0994
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- - Accuracy: 0.9858
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- - F1: 0.9850
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- - Precision: 0.9871
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- - Recall: 0.9829
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  ## Model description
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@@ -44,24 +44,23 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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- - train_batch_size: 16
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  - eval_batch_size: 32
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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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- - lr_scheduler_warmup_steps: 500
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  - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.1153 | 1.0 | 1478 | 0.0675 | 0.9871 | 0.9865 | 0.9837 | 0.9893 |
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- | 0.0632 | 2.0 | 2956 | 0.0508 | 0.9882 | 0.9876 | 0.9811 | 0.9943 |
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- | 0.0397 | 3.0 | 4434 | 0.0546 | 0.9865 | 0.9858 | 0.9810 | 0.9908 |
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- | 0.027 | 4.0 | 5912 | 0.0817 | 0.9875 | 0.9869 | 0.9858 | 0.9879 |
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- | 0.0177 | 5.0 | 7390 | 0.0994 | 0.9858 | 0.9850 | 0.9871 | 0.9829 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: mit
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+ base_model: indobenchmark/indobert-base-p1
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # results
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+ This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0816
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+ - Accuracy: 0.9871
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+ - F1: 0.9865
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+ - Precision: 0.9865
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+ - Recall: 0.9865
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  ## Model description
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  ### Training hyperparameters
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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: 32
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  - eval_batch_size: 32
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.0371 | 1.0 | 739 | 0.0493 | 0.9875 | 0.9869 | 0.9851 | 0.9886 |
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+ | 0.0407 | 2.0 | 1478 | 0.0432 | 0.9868 | 0.9862 | 0.9830 | 0.9893 |
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+ | 0.0446 | 3.0 | 2217 | 0.0647 | 0.9841 | 0.9835 | 0.9735 | 0.9936 |
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+ | 0.031 | 4.0 | 2956 | 0.0766 | 0.9854 | 0.9846 | 0.9892 | 0.9801 |
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+ | 0.0072 | 5.0 | 3695 | 0.0816 | 0.9871 | 0.9865 | 0.9865 | 0.9865 |
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  ### Framework versions
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