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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: XLM_Lexical_CITA_phishlang |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# XLM_Lexical_CITA_phishlang |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5419 |
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- Accuracy: 0.8563 |
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- F1: 0.8533 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 0.4236 | 1.0 | 1138 | 0.3936 | 0.8460 | 0.8325 | |
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| 0.3586 | 2.0 | 2276 | 0.3694 | 0.8562 | 0.8505 | |
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| 0.3234 | 3.0 | 3414 | 0.3493 | 0.8626 | 0.8575 | |
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| 0.2919 | 4.0 | 4552 | 0.3552 | 0.8617 | 0.8554 | |
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| 0.2574 | 5.0 | 5690 | 0.4121 | 0.8615 | 0.8579 | |
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| 0.2283 | 6.0 | 6828 | 0.4162 | 0.8624 | 0.8570 | |
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| 0.2002 | 7.0 | 7966 | 0.4529 | 0.8593 | 0.8552 | |
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| 0.1781 | 8.0 | 9104 | 0.4664 | 0.8610 | 0.8569 | |
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| 0.1639 | 9.0 | 10242 | 0.5102 | 0.8574 | 0.8543 | |
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| 0.1512 | 10.0 | 11380 | 0.5419 | 0.8563 | 0.8533 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.21.0 |
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