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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> |