finetuned-bert-uncased

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Model description

This model is a fine-tuned version of bert-base-uncased on this Kaggle dataset. It achieves the following results on the evaluation set:

• Loss: 0.0507

Intended uses

The model is intended to be used for detecting 6 labels of toxicity. The model takes in a comment as string and predicts the probabilities of the 6 types of toxicity (as float between 0 and 1)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Tokenizers 0.13.3