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@@ -133,9 +133,9 @@ relationship between the members of such pairs. Such corpus has three subsets: *
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  The model's fine-tuning procedure can be summarized in three major subsequent tasks:
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  <ol type="i">
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  <li>**Data Processing:**</li> [ASSIN](https://huggingface.co/datasets/assin)'s *validation* and *train* splits were loaded from the **Hugging Face Hub** and processed afterwards;
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- <li>**Hyperparameter Tuning:**</li> [XLM-RoBERTa-base](https://huggingface.co/xlm-roberta-base)'s hyperparameters were chosen with the help of the [Weights & Biases] API to track the results and upload the fine-tuned models;
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  <li>**Final Model Loading and Testing:**</li>
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- using the *cross-tests* approach described in the [this section](#evaluation), the models' performance were measured using different datasets and metrics.
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  </ol>
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@@ -182,9 +182,7 @@ Testing this model in [ASSIN](https://huggingface.co/datasets/assin)'s test spli
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  ### ASSIN2
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  <!-- Given a pair of sentences $(premise, hypothesis)$, $\hat{f}^{(xlmr\_base)}(premise, hypothesis)$ can be equal to $PARAPHRASE, ENTAILMENT$ or $NONE$ as defined in [Definition 1](#assin_function). -->
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- [ASSIN2](https://huggingface.co/datasets/assin2)'s test split's class label's column has only two possible values: $ENTAILMENT$ and $NONE$. Therefore, in order to test this model in [ASSIN2](https://huggingface.co/datasets/assin2)'s test split some mapping must be done in order to make the [ASSIN2](https://huggingface.co/datasets/assin2)' class labels compatible with the model's inference function.
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-
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- More information on how such mapping is performed will be available in the [referred paper](#model-sources).
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  ### Metrics
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  The model's fine-tuning procedure can be summarized in three major subsequent tasks:
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  <ol type="i">
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  <li>**Data Processing:**</li> [ASSIN](https://huggingface.co/datasets/assin)'s *validation* and *train* splits were loaded from the **Hugging Face Hub** and processed afterwards;
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+ <li>**Hyperparameter Tuning:**</li> [XLM-RoBERTa-base](https://huggingface.co/xlm-roberta-base)'s hyperparameters were chosen with the help of the [Weights & Biases](https://docs.wandb.ai/ref/python/public-api/api) API to track the results and upload the fine-tuned models;
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  <li>**Final Model Loading and Testing:**</li>
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+ The models' performance was evaluated using different datasets and metrics that will be better described in the future paper.
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  </ol>
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  ### ASSIN2
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  <!-- Given a pair of sentences $(premise, hypothesis)$, $\hat{f}^{(xlmr\_base)}(premise, hypothesis)$ can be equal to $PARAPHRASE, ENTAILMENT$ or $NONE$ as defined in [Definition 1](#assin_function). -->
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+ [ASSIN2](https://huggingface.co/datasets/assin2)'s test split's class label's column has only two possible values: *ENTAILMENT* and *NONE*. Therefore some mapping must be done so this model can be tested in [ASSIN2](https://huggingface.co/datasets/assin2)'s test split. More information on how such mapping is performed will be available in the [referred paper](#model-sources).
 
 
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  ### Metrics
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