sentiment-base-4
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: 0.8053
- Accuracy: 0.8922
- Precision: 0.8694
- Recall: 0.8712
- F1: 0.8703
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 |
---|---|---|---|---|---|---|---|
0.371 | 1.0 | 122 | 0.2789 | 0.8847 | 0.8717 | 0.8434 | 0.8557 |
0.214 | 2.0 | 244 | 0.2703 | 0.8947 | 0.8682 | 0.8855 | 0.8760 |
0.141 | 3.0 | 366 | 0.4446 | 0.8747 | 0.8586 | 0.8313 | 0.8431 |
0.093 | 4.0 | 488 | 0.5896 | 0.8697 | 0.8520 | 0.8253 | 0.8368 |
0.0469 | 5.0 | 610 | 0.6099 | 0.8797 | 0.8530 | 0.8599 | 0.8563 |
0.0498 | 6.0 | 732 | 0.6610 | 0.8997 | 0.9016 | 0.8516 | 0.8715 |
0.0257 | 7.0 | 854 | 0.6781 | 0.8872 | 0.8917 | 0.8302 | 0.8532 |
0.0267 | 8.0 | 976 | 0.8200 | 0.8872 | 0.8951 | 0.8277 | 0.8523 |
0.016 | 9.0 | 1098 | 0.5966 | 0.8997 | 0.8740 | 0.8916 | 0.8819 |
0.0132 | 10.0 | 1220 | 0.6437 | 0.9023 | 0.8792 | 0.8883 | 0.8835 |
0.0161 | 11.0 | 1342 | 0.6797 | 0.9073 | 0.8920 | 0.8819 | 0.8867 |
0.0091 | 12.0 | 1464 | 0.6954 | 0.9098 | 0.8999 | 0.8787 | 0.8883 |
0.0101 | 13.0 | 1586 | 0.6751 | 0.9123 | 0.8910 | 0.9004 | 0.8955 |
0.0025 | 14.0 | 1708 | 0.7317 | 0.9023 | 0.8934 | 0.8658 | 0.8780 |
0.0088 | 15.0 | 1830 | 0.6789 | 0.8897 | 0.8670 | 0.8670 | 0.8670 |
0.0017 | 16.0 | 1952 | 0.7505 | 0.8897 | 0.8659 | 0.8695 | 0.8676 |
0.0017 | 17.0 | 2074 | 0.7756 | 0.8897 | 0.8659 | 0.8695 | 0.8676 |
0.0011 | 18.0 | 2196 | 0.8041 | 0.8922 | 0.8673 | 0.8763 | 0.8716 |
0.0017 | 19.0 | 2318 | 0.8064 | 0.8922 | 0.8694 | 0.8712 | 0.8703 |
0.0008 | 20.0 | 2440 | 0.8053 | 0.8922 | 0.8694 | 0.8712 | 0.8703 |
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-4
Base model
indolem/indobert-base-uncased
Finetuned
this model