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--- |
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license: mit |
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base_model: ayameRushia/roberta-base-indonesian-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_roberta_model_fold_1 |
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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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[<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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[<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_roberta_model_fold_1 |
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This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-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: 0.8575 |
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- Accuracy: 0.8868 |
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- Precision: 0.8904 |
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- Recall: 0.8843 |
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- F1: 0.8870 |
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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 | 0.9177 | 0.5472 | 0.7029 | 0.6055 | 0.5274 | |
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| No log | 2.0 | 212 | 0.8990 | 0.7264 | 0.7612 | 0.7252 | 0.7101 | |
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| No log | 3.0 | 318 | 0.7968 | 0.8491 | 0.8478 | 0.8622 | 0.8496 | |
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| No log | 4.0 | 424 | 0.8026 | 0.8396 | 0.8400 | 0.8413 | 0.8353 | |
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| 0.5042 | 5.0 | 530 | 1.0039 | 0.8443 | 0.8579 | 0.8603 | 0.8488 | |
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| 0.5042 | 6.0 | 636 | 0.8274 | 0.8774 | 0.8743 | 0.8850 | 0.8780 | |
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| 0.5042 | 7.0 | 742 | 0.8575 | 0.8868 | 0.8904 | 0.8843 | 0.8870 | |
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| 0.5042 | 8.0 | 848 | 0.9014 | 0.8821 | 0.8806 | 0.8906 | 0.8830 | |
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| 0.5042 | 9.0 | 954 | 0.9622 | 0.8726 | 0.8723 | 0.8859 | 0.8741 | |
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| 0.0373 | 10.0 | 1060 | 0.9673 | 0.8726 | 0.8723 | 0.8859 | 0.8741 | |
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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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