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README.md
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---
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license: apache-2.0
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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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- f1
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model-index:
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- name: distilled-optimized-indobert-classification
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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: 0.8944444444444445
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- name: F1
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type: f1
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value: 0.89395273315396
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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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# distilled-optimized-indobert-classification
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indonlu dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7098
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- Accuracy: 0.8944
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- F1: 0.8940
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4.315104717136378e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 33
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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: 9
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 1.5386 | 1.0 | 688 | 1.0026 | 0.8325 | 0.8332 |
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| 0.8165 | 2.0 | 1376 | 0.7364 | 0.8786 | 0.8782 |
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| 0.4755 | 3.0 | 2064 | 0.8695 | 0.8794 | 0.8767 |
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| 0.3011 | 4.0 | 2752 | 0.8100 | 0.8921 | 0.8899 |
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| 0.1963 | 5.0 | 3440 | 0.8074 | 0.8960 | 0.8954 |
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| 0.1312 | 6.0 | 4128 | 0.8235 | 0.8897 | 0.8906 |
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| 0.0974 | 7.0 | 4816 | 0.7395 | 0.9063 | 0.9067 |
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| 0.0716 | 8.0 | 5504 | 0.7185 | 0.8960 | 0.8953 |
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| 0.0512 | 9.0 | 6192 | 0.7098 | 0.8944 | 0.8940 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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