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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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datasets: |
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- indonlu |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: Model_analisis_sentimen |
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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: 0.9412698412698413 |
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- name: Precision |
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type: precision |
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value: 0.9167407809931684 |
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- name: Recall |
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type: recall |
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value: 0.9068353459620502 |
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- name: F1 |
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type: f1 |
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value: 0.9115530488925131 |
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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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# Model_analisis_sentimen |
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This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4175 |
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- Accuracy: 0.9413 |
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- Precision: 0.9167 |
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- Recall: 0.9068 |
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- F1: 0.9116 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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