---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-binary-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-base-binary-classification

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8437
- Accuracy: 0.7197
- F1 Macro: 0.7136
- Precision Macro: 0.7122
- Recall Macro: 0.7180
- Auc: 0.7698

## 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 OptimizerNames.ADAMW_TORCH_FUSED 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 Macro | Precision Macro | Recall Macro | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:------:|
| No log        | 1.0   | 79   | 0.6399          | 0.6720   | 0.6078   | 0.6827          | 0.6172       | 0.7059 |
| No log        | 2.0   | 158  | 0.5915          | 0.7038   | 0.6997   | 0.7000          | 0.7071       | 0.7527 |
| No log        | 3.0   | 237  | 0.6490          | 0.7420   | 0.7148   | 0.7461          | 0.7089       | 0.7592 |
| No log        | 4.0   | 316  | 0.8437          | 0.7197   | 0.7136   | 0.7122          | 0.7180       | 0.7698 |
| No log        | 5.0   | 395  | 1.2274          | 0.7070   | 0.6369   | 0.7682          | 0.6466       | 0.7648 |
| No log        | 6.0   | 474  | 1.1953          | 0.7038   | 0.6992   | 0.6990          | 0.7059       | 0.7482 |
| 0.3882        | 7.0   | 553  | 1.2941          | 0.7357   | 0.7231   | 0.7257          | 0.7212       | 0.7580 |
| 0.3882        | 8.0   | 632  | 1.4526          | 0.7261   | 0.7150   | 0.7156          | 0.7145       | 0.7441 |
| 0.3882        | 9.0   | 711  | 1.6187          | 0.6975   | 0.6917   | 0.6908          | 0.6967       | 0.7349 |
| 0.3882        | 10.0  | 790  | 1.5593          | 0.7389   | 0.7275   | 0.7289          | 0.7264       | 0.7492 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1