xlm-roberta-base-language-detection-disaster-twitter
This model is a fine-tuned version of papluca/xlm-roberta-base-language-detection on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4869
- F1: 0.7902
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 381 | 0.4407 | 0.7701 |
| 0.4972 | 2.0 | 762 | 0.4186 | 0.7560 |
| 0.3742 | 3.0 | 1143 | 0.4869 | 0.7902 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2+cpu
- Datasets 2.1.0
- Tokenizers 0.15.2