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