---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XLM_Lexical_CITA_phishlang
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# XLM_Lexical_CITA_phishlang

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/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