---
license: apache-2.0
library_name: transformers
tags:
- text-classification
- roberta
- sweep
---
# SweepBestModel

<div align="center">
  <img src="figures/training_curve.png" width="70%" alt="Training Curve" />
</div>

## Overview

This model was selected from a hyperparameter sweep as the best-performing run based on validation accuracy. It is a RoBERTa-based sequence classifier fine-tuned on our internal dataset.

## Training Configuration

- **Learning Rate:** 3e-5
- **Batch Size:** 64
- **Epochs:** 10
- **Best Validation Accuracy:** 0.864

## Benchmark Results

<div align="center">

| Benchmark | Score |
|---|---|
| MNLI (m/mm) | 0.864 |
| SST-2 | 0.864 |
| QQP | 0.864 |
| QNLI | 0.864 |
| RTE | 0.864 |
| CoLA | 0.864 |
| STS-B | 0.864 |
| MRPC | 0.864 |

</div>

## Usage

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("SweepBestModel-Repo")
tokenizer = AutoTokenizer.from_pretrained("SweepBestModel-Repo")
```

## Figures

<div align="center">
  <img src="figures/confusion_matrix.png" width="45%" alt="Confusion Matrix" />
  <img src="figures/loss_curve.png" width="45%" alt="Loss Curve" />
</div>