| | --- |
| | language: |
| | - id |
| | license: mit |
| | base_model: indolem/indobert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: sentiment-base-2 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # sentiment-base-2 |
| |
|
| | This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8886 |
| | - Accuracy: 0.8922 |
| | - Precision: 0.8719 |
| | - Recall: 0.8662 |
| | - F1: 0.8690 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-05 |
| | - train_batch_size: 30 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.3808 | 1.0 | 122 | 0.3794 | 0.8647 | 0.8737 | 0.7917 | 0.8186 | |
| | | 0.221 | 2.0 | 244 | 0.2851 | 0.8722 | 0.8562 | 0.8271 | 0.8395 | |
| | | 0.1363 | 3.0 | 366 | 0.3832 | 0.8947 | 0.8757 | 0.8680 | 0.8717 | |
| | | 0.099 | 4.0 | 488 | 0.4968 | 0.8972 | 0.8869 | 0.8598 | 0.8717 | |
| | | 0.0702 | 5.0 | 610 | 0.5205 | 0.8697 | 0.8503 | 0.8278 | 0.8377 | |
| | | 0.0469 | 6.0 | 732 | 0.5740 | 0.8747 | 0.8552 | 0.8363 | 0.8448 | |
| | | 0.0328 | 7.0 | 854 | 0.6012 | 0.8847 | 0.8581 | 0.8684 | 0.8629 | |
| | | 0.0284 | 8.0 | 976 | 0.5403 | 0.8972 | 0.8812 | 0.8673 | 0.8738 | |
| | | 0.019 | 9.0 | 1098 | 0.5909 | 0.8922 | 0.8657 | 0.8813 | 0.8728 | |
| | | 0.016 | 10.0 | 1220 | 0.8931 | 0.8822 | 0.8694 | 0.8392 | 0.8521 | |
| | | 0.0167 | 11.0 | 1342 | 0.6618 | 0.8972 | 0.8781 | 0.8723 | 0.8751 | |
| | | 0.0168 | 12.0 | 1464 | 0.7513 | 0.9023 | 0.8842 | 0.8783 | 0.8812 | |
| | | 0.0064 | 13.0 | 1586 | 0.7513 | 0.8997 | 0.8819 | 0.8741 | 0.8778 | |
| | | 0.0078 | 14.0 | 1708 | 0.8152 | 0.8947 | 0.8789 | 0.8630 | 0.8704 | |
| | | 0.0064 | 15.0 | 1830 | 0.7460 | 0.8997 | 0.8778 | 0.8816 | 0.8797 | |
| | | 0.0055 | 16.0 | 1952 | 0.8232 | 0.8922 | 0.8734 | 0.8637 | 0.8683 | |
| | | 0.006 | 17.0 | 2074 | 0.8421 | 0.8947 | 0.8757 | 0.8680 | 0.8717 | |
| | | 0.0052 | 18.0 | 2196 | 0.8442 | 0.8872 | 0.8624 | 0.8677 | 0.8650 | |
| | | 0.0035 | 19.0 | 2318 | 0.8841 | 0.8897 | 0.8682 | 0.8645 | 0.8663 | |
| | | 0.0013 | 20.0 | 2440 | 0.8886 | 0.8922 | 0.8719 | 0.8662 | 0.8690 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.39.3 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.15.2 |
| |
|
