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metadata
license: apache-2.0
tags:
  - classification
  - generated_from_trainer
datasets:
  - hate_speech_offensive
metrics:
  - accuracy
model-index:
  - name: clasificador-hate_speech_offensive
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: hate_speech_offensive
          type: hate_speech_offensive
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9201129715553762

clasificador-hate_speech_offensive

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

  • Loss: 0.3191
  • Accuracy: 0.9201

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3425 1.0 2479 0.2982 0.9157
0.2783 2.0 4958 0.2695 0.9179
0.2321 3.0 7437 0.3191 0.9201

Framework versions

  • Transformers 4.27.2
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2