---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fm-tc-authenticv2
  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. -->

# fm-tc-authenticv2

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: 0.4353
- Accuracy: 0.91
- Precision: 0.9121
- Recall: 0.9100
- F1: 0.9096

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6462        | 1.0   | 500  | 0.6519          | 0.826    | 0.8439    | 0.8260 | 0.8181 |
| 0.5197        | 2.0   | 1000 | 0.4539          | 0.898    | 0.9012    | 0.8980 | 0.8970 |
| 0.3199        | 3.0   | 1500 | 0.4931          | 0.9      | 0.9067    | 0.9    | 0.9004 |
| 0.1987        | 4.0   | 2000 | 0.4353          | 0.91     | 0.9121    | 0.9100 | 0.9096 |
| 0.0944        | 5.0   | 2500 | 0.4598          | 0.92     | 0.9223    | 0.9200 | 0.9193 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1