hasoc19-xlm-roberta-base-targinsult1
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7512
- Accuracy: 0.7096
- Precision: 0.6720
- Recall: 0.6675
- F1: 0.6695
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 263 | 0.5619 | 0.6996 | 0.6660 | 0.6717 | 0.6684 |
| 0.5931 | 2.0 | 526 | 0.5350 | 0.7239 | 0.6880 | 0.6576 | 0.6655 |
| 0.5931 | 3.0 | 789 | 0.5438 | 0.7239 | 0.6872 | 0.6644 | 0.6714 |
| 0.5101 | 4.0 | 1052 | 0.5595 | 0.7196 | 0.6866 | 0.6909 | 0.6886 |
| 0.5101 | 5.0 | 1315 | 0.5580 | 0.7186 | 0.6818 | 0.6743 | 0.6774 |
| 0.4313 | 6.0 | 1578 | 0.6000 | 0.7039 | 0.6679 | 0.6692 | 0.6686 |
| 0.4313 | 7.0 | 1841 | 0.6429 | 0.7082 | 0.6765 | 0.6841 | 0.6794 |
| 0.3591 | 8.0 | 2104 | 0.6626 | 0.7115 | 0.6772 | 0.6803 | 0.6786 |
| 0.3591 | 9.0 | 2367 | 0.7231 | 0.7139 | 0.6764 | 0.6700 | 0.6727 |
| 0.3016 | 10.0 | 2630 | 0.7512 | 0.7096 | 0.6720 | 0.6675 | 0.6695 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1