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---
language: 
  - en
thumbnail: "url to a thumbnail used in social sharing"
tags:
- classification
license: "mit"
datasets:
- SetFit/qqp
models:
- microsoft/deberta-v3-base
metrics:
- accuracy
- loss
widget:
- text: How is the life of a math student? Could you describe your own experiences?
- text: Which level of preparation is enough for the exam jlpt5?
  example_title: "Classification"
---

A fine-tuned model based on the **DeBERTaV3** model of Microsoft and fine-tuned on **Glue QQP**, which detects the linguistical similarities between two questions and whether they are similar questions or duplicates.

## Model Hyperparameters

```python
epoch=4
per_device_train_batch_size=32
per_device_eval_batch_size=16
lr=2e-5
weight_decay=1e-2
gradient_checkpointing=True
gradient_accumulation_steps=8
```
## Model Performance

```JSON
{"Training Loss": 0.132400,
 "Validation Loss": 0.217410,
 "Validation Accuracy": 0.917969
}
```

## Model Dependencies

```JSON
{"Main Model": "microsoft/deberta-v3-base",
 "Dataset": "SetFit/qqp"
}
```