bert-base-multilingual-cased-reddit-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: 0.4558
- Accuracy: 0.7829
- F1: 0.5338
- Precision: 0.5764
- Recall: 0.4972
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 |
0.4935 |
1.0 |
309 |
0.4739 |
0.7711 |
0.5186 |
0.5472 |
0.4929 |
0.4203 |
2.0 |
618 |
0.4527 |
0.7895 |
0.5547 |
0.5892 |
0.5241 |
0.3469 |
3.0 |
927 |
0.5105 |
0.7923 |
0.4957 |
0.6316 |
0.4079 |
0.2754 |
4.0 |
1236 |
0.5126 |
0.7746 |
0.5254 |
0.5552 |
0.4986 |
0.2208 |
5.0 |
1545 |
0.6012 |
0.7803 |
0.5064 |
0.5782 |
0.4504 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0