sentiment-base-2
This model is a fine-tuned version of 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
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Model tree for apwic/sentiment-base-2
Base model
indolem/indobert-base-uncased
Finetuned
this model