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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: 22best_berita_bert_model_fold_5 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]() |
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# 22best_berita_bert_model_fold_5 |
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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: 1.2244 |
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- Accuracy: 0.8436 |
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- Precision: 0.8477 |
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- Recall: 0.8429 |
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- F1: 0.8431 |
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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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| No log | 1.0 | 106 | 0.8179 | 0.6919 | 0.7903 | 0.6727 | 0.6450 | |
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| No log | 2.0 | 212 | 0.5844 | 0.7773 | 0.7841 | 0.7778 | 0.7766 | |
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| No log | 3.0 | 318 | 1.0969 | 0.7393 | 0.7562 | 0.7439 | 0.7378 | |
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| No log | 4.0 | 424 | 0.9975 | 0.8246 | 0.8247 | 0.8236 | 0.8232 | |
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| 0.404 | 5.0 | 530 | 1.1275 | 0.8104 | 0.8108 | 0.8067 | 0.8071 | |
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| 0.404 | 6.0 | 636 | 1.1943 | 0.8199 | 0.8188 | 0.8191 | 0.8189 | |
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| 0.404 | 7.0 | 742 | 1.2244 | 0.8436 | 0.8477 | 0.8429 | 0.8431 | |
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| 0.404 | 8.0 | 848 | 1.2554 | 0.8341 | 0.8370 | 0.8335 | 0.8336 | |
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| 0.404 | 9.0 | 954 | 1.2681 | 0.8294 | 0.8316 | 0.8288 | 0.8289 | |
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| 0.0067 | 10.0 | 1060 | 1.2894 | 0.8246 | 0.8264 | 0.8241 | 0.8242 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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