indobert-large-p1-twitter-indonesia-sarcastic
This model is a fine-tuned version of indobenchmark/indobert-large-p1 on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3207
- Accuracy: 0.8643
- F1: 0.7160
- Precision: 0.7480
- Recall: 0.6866
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 |
0.5836 |
1.0 |
59 |
0.4153 |
0.8060 |
0.5738 |
0.6364 |
0.5224 |
0.3766 |
2.0 |
118 |
0.3353 |
0.8433 |
0.5962 |
0.8378 |
0.4627 |
0.2476 |
3.0 |
177 |
0.3114 |
0.8619 |
0.6942 |
0.7778 |
0.6269 |
0.1356 |
4.0 |
236 |
0.3279 |
0.8694 |
0.7328 |
0.75 |
0.7164 |
0.0536 |
5.0 |
295 |
0.4265 |
0.8582 |
0.7164 |
0.7164 |
0.7164 |
0.0157 |
6.0 |
354 |
0.6448 |
0.8619 |
0.6667 |
0.8409 |
0.5522 |
0.0076 |
7.0 |
413 |
0.5739 |
0.8619 |
0.7218 |
0.7273 |
0.7164 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0