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README.md
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- assin2
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---
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This is the [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) model finetuned for
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Recognizing Textual Entailment with the [ASSIN 2](https://huggingface.co/datasets/assin2) dataset.
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This model is suitable for Portuguese.
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- Git Repo: [Evaluation of Portuguese Language Models](https://github.com/ruanchaves/eplm).
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- Demo: [
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### **Labels**:
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* 0 : There is no entailment between premise and hypothesis.
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print(f"{i+1}) Label: {l} Score: {np.round(float(s), 4)}")
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```
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Output:
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```
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1) Label: 1 Score: 0.9998
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2) Label: 0 Score: 0.0002
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```
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## Citation
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Our research is ongoing, and we are currently working on describing our experiments in a paper, which will be published soon.
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author = {Chaves Rodrigues, Ruan and Tanti, Marc and Agerri, Rodrigo},
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doi = {10.5281/zenodo.7781848},
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month = {3},
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title =
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url = {https://github.com/ruanchaves/eplm},
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version = {1.0.0},
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year = {2023}
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- assin2
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---
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# mDeBERTa v3 base for Recognizing Textual Entailment
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This is the [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) model finetuned for
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Recognizing Textual Entailment with the [ASSIN 2](https://huggingface.co/datasets/assin2) dataset.
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This model is suitable for Portuguese.
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- Git Repo: [Evaluation of Portuguese Language Models](https://github.com/ruanchaves/eplm).
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- Demo: [Portuguese Textual Entailment](https://ruanchaves-portuguese-textual-entailment.hf.space)
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### **Labels**:
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* 0 : There is no entailment between premise and hypothesis.
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print(f"{i+1}) Label: {l} Score: {np.round(float(s), 4)}")
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```
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## Citation
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Our research is ongoing, and we are currently working on describing our experiments in a paper, which will be published soon.
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author = {Chaves Rodrigues, Ruan and Tanti, Marc and Agerri, Rodrigo},
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doi = {10.5281/zenodo.7781848},
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month = {3},
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title = ,
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url = {https://github.com/ruanchaves/eplm},
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version = {1.0.0},
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year = {2023}
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