XLM_Lexical_CITA_phishlang
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5419
- Accuracy: 0.8563
- F1: 0.8533
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.4236 | 1.0 | 1138 | 0.3936 | 0.8460 | 0.8325 |
0.3586 | 2.0 | 2276 | 0.3694 | 0.8562 | 0.8505 |
0.3234 | 3.0 | 3414 | 0.3493 | 0.8626 | 0.8575 |
0.2919 | 4.0 | 4552 | 0.3552 | 0.8617 | 0.8554 |
0.2574 | 5.0 | 5690 | 0.4121 | 0.8615 | 0.8579 |
0.2283 | 6.0 | 6828 | 0.4162 | 0.8624 | 0.8570 |
0.2002 | 7.0 | 7966 | 0.4529 | 0.8593 | 0.8552 |
0.1781 | 8.0 | 9104 | 0.4664 | 0.8610 | 0.8569 |
0.1639 | 9.0 | 10242 | 0.5102 | 0.8574 | 0.8543 |
0.1512 | 10.0 | 11380 | 0.5419 | 0.8563 | 0.8533 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.21.0
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Model tree for phunganhsang/XLM_Lexical_CITA_phishlang
Base model
FacebookAI/xlm-roberta-base