xlm-roberta-base-reddit-indonesia-sarcastic
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5093
- Accuracy: 0.8031
- F1: 0.5690
- Precision: 0.6284
- Recall: 0.5198
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 |
|---|---|---|---|---|---|---|---|
| 0.5174 | 1.0 | 309 | 0.4618 | 0.7725 | 0.4641 | 0.5650 | 0.3938 |
| 0.4462 | 2.0 | 618 | 0.4407 | 0.7994 | 0.5428 | 0.6316 | 0.4759 |
| 0.3952 | 3.0 | 927 | 0.4690 | 0.8037 | 0.4991 | 0.69 | 0.3909 |
| 0.3525 | 4.0 | 1236 | 0.4905 | 0.8079 | 0.5152 | 0.6990 | 0.4079 |
| 0.3102 | 5.0 | 1545 | 0.4741 | 0.8122 | 0.5917 | 0.6486 | 0.5439 |
| 0.2645 | 6.0 | 1854 | 0.4964 | 0.8101 | 0.5976 | 0.6358 | 0.5637 |
| 0.2168 | 7.0 | 2163 | 0.5216 | 0.8079 | 0.5824 | 0.6385 | 0.5354 |
| 0.1759 | 8.0 | 2472 | 0.6826 | 0.8044 | 0.5818 | 0.6254 | 0.5439 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0