gonzalez-agirre
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Update README.md
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README.md
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@@ -102,6 +102,7 @@ example = "Me llamo francisco javier y vivo en madrid."
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ner_results = nlp(example)
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pprint(ner_results)
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```
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## Limitations and bias
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At the time of submission, no measures have been taken to estimate the bias embedded in the model. However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated.
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The dataset used for training and evaluation is the one from the [CAPITEL competition at IberLEF 2020](https://sites.google.com/view/capitel2020) (sub-task 1). We lowercased and uppercased the dataset, and added the additional sentences to the training.
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### Training procedure
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The model was trained with a batch size of 16 and a learning rate of
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## Evaluation
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ner_results = nlp(example)
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pprint(ner_results)
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```
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## Limitations and bias
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At the time of submission, no measures have been taken to estimate the bias embedded in the model. However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated.
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The dataset used for training and evaluation is the one from the [CAPITEL competition at IberLEF 2020](https://sites.google.com/view/capitel2020) (sub-task 1). We lowercased and uppercased the dataset, and added the additional sentences to the training.
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### Training procedure
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The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5 epochs. We then selected the best checkpoint using the downstream task metric in the corresponding development set and then evaluated it on the test set.
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## Evaluation
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