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@@ -8,6 +8,13 @@ licenses:
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  task_categories:
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  - text-classification
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  ---
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  # Offensive language dataset of Croatian, English and Slovenian comments FRENK 1.0
@@ -18,8 +25,8 @@ The data in each language (Croatian (hr), English (en), Slovenian (sl), and topi
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  For this dataset only the English data was used. Training segment has been split into beginning 90% (published here as training split) and end 10% (published here as dev split).
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- # Usage in `Transformers`
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  ```python
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  import datasets
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  ds = datasets.load_dataset("classla/FRENK-hate-en","binary")
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  ```
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  The original labels are available if the dataset is loaded with the `multiclass` option:
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  ```python
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  import datasets
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  ds = datasets.load_dataset("classla/FRENK-hate-en","multiclass").
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  ```
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- # Data structure
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  * `text`: text
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  * `target`: who is the target of the hate-speech text ("no target", "commenter", "target" (migrants or LGBT, depending on the topic), or "related to" (again, the topic))
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  * `topic`: whether the text relates to lgbt or migrants hate-speech domains
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  * `label`: label of the text instance, see above.
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- # Data instance
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  ```
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  {'text': "Not everyone has the option of a rainbow reaction; I don't but wish I did.",
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  'label': 0}
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  ```
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-
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  When using this dataset please cite the following paper:
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  task_categories:
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  - text-classification
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+ task_ids:
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+ - text-classification-other-hate-speech-detection
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+ - text-classification-other-offensive-languagage
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+
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+ size_categories:
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+ - 1K<n<10K
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+
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  ---
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  # Offensive language dataset of Croatian, English and Slovenian comments FRENK 1.0
 
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  For this dataset only the English data was used. Training segment has been split into beginning 90% (published here as training split) and end 10% (published here as dev split).
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+ ## Usage in `Transformers`
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  ```python
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  import datasets
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  ds = datasets.load_dataset("classla/FRENK-hate-en","binary")
 
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  ```
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  The original labels are available if the dataset is loaded with the `multiclass` option:
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+ ```python
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+ import datasets
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+ ds = datasets.load_dataset("5roop/FRENK-hate-en","multiclass").
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+ ```
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+
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+ In this case the encoding used is:
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+ ```python
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+ _CLASS_MAP_MULTICLASS = {
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+ 'Acceptable speech': 0,
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+ 'Inappropriate': 1,
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+ 'Background offensive': 2,
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+ 'Other offensive': 3,
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+ 'Background violence': 4,
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+ 'Other violence': 5,
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+ }
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+ ```
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+
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+
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+ The original labels are available if the dataset is loaded with the `multiclass` option:
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+
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  ```python
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  import datasets
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  ds = datasets.load_dataset("classla/FRENK-hate-en","multiclass").
 
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  ```
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+ ## Data structure
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  * `text`: text
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  * `target`: who is the target of the hate-speech text ("no target", "commenter", "target" (migrants or LGBT, depending on the topic), or "related to" (again, the topic))
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  * `topic`: whether the text relates to lgbt or migrants hate-speech domains
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  * `label`: label of the text instance, see above.
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+ ## Data instance
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  ```
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  {'text': "Not everyone has the option of a rainbow reaction; I don't but wish I did.",
 
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  'label': 0}
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  ```
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+ ## Citation information
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  When using this dataset please cite the following paper:
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