---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: fold_4_model_roberta
  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. -->

# fold_4_model_roberta

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6094
- F1: 0.7390
- Roc Auc: 0.8019
- Accuracy: 0.4144

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.0424        | 1.0   | 111  | 0.6255          | 0.7252 | 0.7940  | 0.3784   |
| 0.0322        | 2.0   | 222  | 0.6856          | 0.7102 | 0.7831  | 0.3514   |
| 0.0205        | 3.0   | 333  | 0.6094          | 0.7390 | 0.8019  | 0.4144   |
| 0.0169        | 4.0   | 444  | 0.6782          | 0.7135 | 0.7842  | 0.3694   |
| 0.0149        | 5.0   | 555  | 0.6594          | 0.7262 | 0.7939  | 0.3784   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0