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---
language:
- en
license: cc-by-4.0
tags:
- classification
datasets:
- SetFit/qqp
metrics:
- accuracy
- loss
thumbnail: https://github.com/AI-Ahmed
models:
- microsoft/deberta-v3-base
pipeline_tag: text-classification
widget:
- text: How is the life of a math student? Could you describe your own experiences?
Which level of preparation is enough for the exam jlpt5?
example_title: Difference Detection.
- text: What can one do after MBBS? What do i do after my MBBS?
example_title: Duplicates Detection.
model-index:
- name: deberta-v3-base-funetuned-cls-qqa
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: qqp
type: qqp
config: sst2
split: validation
metrics:
- type: accuracy
value: 0.917969
name: Accuracy
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzA2OWM4ZjJkYzZjNmM3YmNkODNhODYzOTMxY2RjZTZmODg4ODA4ZjJmNjFhNjkwZjFmZjk3YjBiNzhjNDAzOCIsInZlcnNpb24iOjF9.TqdmhhV_3fTWYHtM7SJj35ICZgZ6Ux7qYXwPHu8j0MkDmSeZfTniFCqB8LO8pqM1bK5iHQV1-vggZUdMu4spCA
- type: loss
value: 0.21741
name: loss
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGQzZGZjNzZjNzFjOWViNjkyNGIxMGE5ZjA5ODAxOTNiZGQ5OTY4NWM1YThlZGEyZGRjOGE2MjkwYTRjN2Q2MyIsInZlcnNpb24iOjF9.ZxmqxdbOhAA8Ywz8_Q3aFaFG2kmTogFdWjlHgEa2JnGQWhL39VVtcn6A8gtekE_e3z5jsaNS4EnSzYVSWJZjAQ
---
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 duplicates questions or different.
## 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"
}
```
## Training Monitoring & Performance
- [wandb - deberta_qqa_classification](https://wandb.ai/ai-ahmed/deberta_qqa_classification?workspace=user-ai-ahmed)
## Model Testing
```python
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model_name = "AI-Ahmed/deberta-v3-base-funetuned-cls-qqa"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenized_input = tokenizer("How is the life of a math student? Could you describe your own experiences? Which level of preparation is enough for the exam jlpt5?", return_tensors="pt")
with torch.no_grad():
logits = model(**tokenized_input).logits
predicted_class_id = logits.argmax().item()
model.config.id2label[predicted_class_id]
```
## Information Citation
```bibtex
@inproceedings{
he2021deberta,
title={DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION},
author={Pengcheng He and Xiaodong Liu and Jianfeng Gao and Weizhu Chen},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=XPZIaotutsD}
}
``` |