Andika Mandala Putra
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End of training
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README.md
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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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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: indobert-base-uncased-finetuned-indonlu-smsa
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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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config: smsa
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split: validation
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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: 0.9214285714285714
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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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# indobert-base-uncased-finetuned-indonlu-smsa
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the indonlu dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2232
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- Accuracy: 0.9214
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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: 1e-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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- lr_scheduler_warmup_steps: 2000
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 344 | 0.6858 | 0.7063 |
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| 0.8162 | 2.0 | 688 | 0.3510 | 0.8611 |
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| 0.3579 | 3.0 | 1032 | 0.2232 | 0.9214 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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