---
library_name: transformers
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-binary-classification
  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-large-binary-classification

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6983
- Accuracy: 0.7580
- F1 Macro: 0.7453
- Precision Macro: 0.7498
- Recall Macro: 0.7425
- Auc: 0.7941

## 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   | 0.6751          | 0.5955   | 0.3733   | 0.2978          | 0.5          | 0.6194 |
| No log        | 2.0   | 158  | 0.6642          | 0.5955   | 0.3733   | 0.2978          | 0.5          | 0.6210 |
| No log        | 3.0   | 237  | 0.5609          | 0.7102   | 0.6895   | 0.7003          | 0.6859       | 0.7701 |
| No log        | 4.0   | 316  | 0.5676          | 0.7070   | 0.6907   | 0.6954          | 0.6883       | 0.7734 |
| No log        | 5.0   | 395  | 0.6983          | 0.7580   | 0.7453   | 0.7498          | 0.7425       | 0.7941 |
| No log        | 6.0   | 474  | 0.7766          | 0.7420   | 0.7319   | 0.7322          | 0.7316       | 0.7802 |
| 0.4887        | 7.0   | 553  | 1.1879          | 0.7452   | 0.7266   | 0.7399          | 0.7217       | 0.7761 |
| 0.4887        | 8.0   | 632  | 1.6676          | 0.7484   | 0.7242   | 0.7504          | 0.7180       | 0.7789 |
| 0.4887        | 9.0   | 711  | 1.6440          | 0.7548   | 0.7364   | 0.7511          | 0.7310       | 0.7889 |
| 0.4887        | 10.0  | 790  | 1.7092          | 0.7548   | 0.7364   | 0.7511          | 0.7310       | 0.7928 |


### Framework versions

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