bert-base-multilingual-cased-twitter-indonesia-sarcastic
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4720
- Accuracy: 0.8290
- F1: 0.6462
- Precision: 0.6667
- Recall: 0.6269
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
Precision |
Recall |
0.5333 |
1.0 |
59 |
0.4792 |
0.75 |
0.0 |
0.0 |
0.0 |
0.4642 |
2.0 |
118 |
0.4418 |
0.7910 |
0.3 |
0.9231 |
0.1791 |
0.3961 |
3.0 |
177 |
0.4319 |
0.8134 |
0.5192 |
0.7297 |
0.4030 |
0.325 |
4.0 |
236 |
0.5264 |
0.7463 |
0.6180 |
0.4955 |
0.8209 |
0.2432 |
5.0 |
295 |
0.4624 |
0.8246 |
0.6299 |
0.6667 |
0.5970 |
0.1819 |
6.0 |
354 |
0.4261 |
0.8731 |
0.7069 |
0.8367 |
0.6119 |
0.148 |
7.0 |
413 |
0.5371 |
0.8545 |
0.6777 |
0.7593 |
0.6119 |
0.0995 |
8.0 |
472 |
0.6810 |
0.8396 |
0.6767 |
0.6818 |
0.6716 |
0.0843 |
9.0 |
531 |
0.8350 |
0.8209 |
0.5385 |
0.7568 |
0.4179 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0