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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: indonesian-brand-indoBERT-finetuned |
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results: [] |
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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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# indonesian-brand-indoBERT-finetuned |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6848 |
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- Accuracy: 0.8601 |
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- Precision: 0.8601 |
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- Recall: 0.8601 |
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- F1: 0.8601 |
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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: 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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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 304 | 0.4935 | 0.8132 | 0.8132 | 0.8132 | 0.8132 | |
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| 0.5911 | 2.0 | 608 | 0.4046 | 0.8362 | 0.8362 | 0.8362 | 0.8362 | |
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| 0.5911 | 3.0 | 912 | 0.4873 | 0.8305 | 0.8305 | 0.8305 | 0.8305 | |
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| 0.3204 | 4.0 | 1216 | 0.4774 | 0.8560 | 0.8560 | 0.8560 | 0.8560 | |
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| 0.2154 | 5.0 | 1520 | 0.5759 | 0.8486 | 0.8486 | 0.8486 | 0.8486 | |
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| 0.2154 | 6.0 | 1824 | 0.6334 | 0.8568 | 0.8568 | 0.8568 | 0.8568 | |
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| 0.1454 | 7.0 | 2128 | 0.6848 | 0.8601 | 0.8601 | 0.8601 | 0.8601 | |
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| 0.1454 | 8.0 | 2432 | 0.7325 | 0.8560 | 0.8560 | 0.8560 | 0.8560 | |
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| 0.0982 | 9.0 | 2736 | 0.7782 | 0.8568 | 0.8568 | 0.8568 | 0.8568 | |
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| 0.0729 | 10.0 | 3040 | 0.7979 | 0.8584 | 0.8584 | 0.8584 | 0.8584 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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