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--- |
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license: mit |
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base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa |
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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: best_berita_bert_model_fold_3 |
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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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# best_berita_bert_model_fold_3 |
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This model is a fine-tuned version of [ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1732 |
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- Accuracy: 0.9808 |
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- Precision: 0.9809 |
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- Recall: 0.9811 |
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- F1: 0.9809 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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 | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.5469 | 1.0 | 601 | 0.2814 | 0.9409 | 0.9416 | 0.9414 | 0.9410 | |
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| 0.21 | 2.0 | 1202 | 0.1697 | 0.9600 | 0.9602 | 0.9605 | 0.9600 | |
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| 0.1002 | 3.0 | 1803 | 0.2227 | 0.9667 | 0.9674 | 0.9673 | 0.9666 | |
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| 0.0847 | 4.0 | 2404 | 0.2771 | 0.9584 | 0.9599 | 0.9592 | 0.9581 | |
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| 0.029 | 5.0 | 3005 | 0.1732 | 0.9808 | 0.9809 | 0.9811 | 0.9809 | |
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| 0.0095 | 6.0 | 3606 | 0.2415 | 0.9734 | 0.9737 | 0.9738 | 0.9733 | |
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| 0.0134 | 7.0 | 4207 | 0.2048 | 0.9767 | 0.9769 | 0.9771 | 0.9766 | |
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| 0.0001 | 8.0 | 4808 | 0.2916 | 0.9692 | 0.9697 | 0.9698 | 0.9691 | |
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| 0.0039 | 9.0 | 5409 | 0.2201 | 0.9784 | 0.9786 | 0.9787 | 0.9784 | |
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| 0.0 | 10.0 | 6010 | 0.2293 | 0.9742 | 0.9745 | 0.9746 | 0.9742 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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