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ml6team/distilbert-base-dutch-cased-toxic-comments
distilbert-base-dutch-cased-toxic-comments is a text classification model from ml6team. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
This model was created with the purpose to detect toxic or potentially harmful comments.
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From the Hugging Face model README
This model was created with the purpose to detect toxic or potentially harmful comments.
For this model, we finetuned a multilingual distilbert model distilbert-base-multilingual-cased on the translated Jigsaw Toxicity dataset.
The original dataset was translated using the appropriate MariantMT model.
The model was trained for 2 epochs, on 90% of the dataset, with the following arguments:
training_args = TrainingArguments(
learning_rate=3e-5,
per_device_train_batch_size=16,
per_device_eval_batch_size=16,
gradient_accumulation_steps=4,
load_best_model_at_end=True,
metric_for_best_model="recall",
epochs=2,
evaluation_strategy="steps",
save_strategy="steps",
save_total_limit=10,
logging_steps=100,
eval_steps=250,
save_steps=250,
weight_decay=0.001,
report_to="wandb")
Model evaluation was done on 1/10th of the dataset, which served as the test dataset.
| Accuracy | F1 Score | Recall | Precision |
|---|---|---|---|
| 95.75 | 78.88 | 77.23 | 80.61 |
Unfortunately we cannot open-source the dataset, since we are bound by the underlying Jigsaw license.