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--- |
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license: mit |
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base_model: indobenchmark/indobert-base-p2 |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: fitur_model |
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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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# fitur_model |
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This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4122 |
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- Accuracy: 0.8077 |
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- F1: 0.8789 |
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- Precision: 0.8355 |
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- Recall: 0.9270 |
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 92 | 0.4122 | 0.8077 | 0.8789 | 0.8355 | 0.9270 | |
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| No log | 2.0 | 184 | 0.4881 | 0.8022 | 0.8657 | 0.8855 | 0.8467 | |
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| No log | 3.0 | 276 | 0.6448 | 0.8297 | 0.8912 | 0.8581 | 0.9270 | |
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| No log | 4.0 | 368 | 0.8912 | 0.8132 | 0.8786 | 0.8601 | 0.8978 | |
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| No log | 5.0 | 460 | 1.2147 | 0.7967 | 0.8702 | 0.8378 | 0.9051 | |
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| 0.1904 | 6.0 | 552 | 1.3269 | 0.8077 | 0.8754 | 0.8542 | 0.8978 | |
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| 0.1904 | 7.0 | 644 | 1.4276 | 0.7967 | 0.8693 | 0.8425 | 0.8978 | |
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| 0.1904 | 8.0 | 736 | 1.4681 | 0.8022 | 0.8732 | 0.8435 | 0.9051 | |
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| 0.1904 | 9.0 | 828 | 1.4804 | 0.7967 | 0.8693 | 0.8425 | 0.8978 | |
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| 0.1904 | 10.0 | 920 | 1.4867 | 0.8022 | 0.8732 | 0.8435 | 0.9051 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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