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README.md
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metrics:
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- accuracy
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- loss
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pipeline_tag: text-classification
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widget:
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- 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?
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- [wandb - deberta_qqa_classification](https://wandb.ai/ai-ahmed/deberta_qqa_classification?workspace=user-ai-ahmed)
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## Information Citation
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```bibtex
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year={2021},
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url={https://openreview.net/forum?id=XPZIaotutsD}
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}
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-
```
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metrics:
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- accuracy
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- loss
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model-index:
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- name: deberta-v3-base-funetuned-cls-qqa
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: qqp
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type: qqp
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config: sst2
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split: validation
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.917969
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verified: true
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- name: loss
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type: loss
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value: 0.217410
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verified: true
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pipeline_tag: text-classification
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widget:
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- 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?
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- [wandb - deberta_qqa_classification](https://wandb.ai/ai-ahmed/deberta_qqa_classification?workspace=user-ai-ahmed)
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## Model Testing
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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model_name = "AI-Ahmed/deberta-v3-base-funetuned-cls-qqa"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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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")
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with torch.no_grad():
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logits = model(**tokenized_input).logits
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predicted_class_id = logits.argmax().item()
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model.config.id2label[predicted_class_id]
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```
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## Information Citation
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```bibtex
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year={2021},
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url={https://openreview.net/forum?id=XPZIaotutsD}
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}
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```
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