---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base-kennedy2020constructing
  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. -->

# roberta-base-kennedy2020constructing

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: 0.2110
- Accuracy: 0.9738
- Roc Auc: 0.9915
- Precision: 0.9680
- Recall: 0.9592
- F1: 0.9636

## 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: 96
- eval_batch_size: 128
- 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_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Roc Auc | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:---------:|:------:|:------:|
| 0.2481        | 1.0   | 1144  | 0.2172          | 0.9001   | 0.9676  | 0.9266    | 0.7861 | 0.8506 |
| 0.1822        | 2.0   | 2288  | 0.1604          | 0.9380   | 0.9836  | 0.9252    | 0.9017 | 0.9133 |
| 0.1085        | 3.0   | 3432  | 0.1343          | 0.9575   | 0.9893  | 0.9627    | 0.9180 | 0.9398 |
| 0.0674        | 4.0   | 4576  | 0.1225          | 0.9649   | 0.9918  | 0.9477    | 0.9558 | 0.9517 |
| 0.0502        | 5.0   | 5720  | 0.1455          | 0.9688   | 0.9919  | 0.9561    | 0.9576 | 0.9569 |
| 0.0365        | 6.0   | 6864  | 0.1370          | 0.9698   | 0.9921  | 0.9676    | 0.9481 | 0.9578 |
| 0.0258        | 7.0   | 8008  | 0.1719          | 0.9706   | 0.9925  | 0.9615    | 0.9570 | 0.9592 |
| 0.0184        | 8.0   | 9152  | 0.1737          | 0.9731   | 0.9922  | 0.9686    | 0.9567 | 0.9626 |
| 0.0141        | 9.0   | 10296 | 0.2051          | 0.9734   | 0.9916  | 0.9673    | 0.9588 | 0.9630 |
| 0.01          | 10.0  | 11440 | 0.2110          | 0.9738   | 0.9915  | 0.9680    | 0.9592 | 0.9636 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0