README.md

metadata

library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - hate_speech_portuguese
metrics:
  - accuracy
model-index:
  - name: bert-hate-speech-test
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: hate_speech_portuguese
          type: hate_speech_portuguese
          config: default
          split: train[:10%]
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5964912280701754

bert-hate-speech-test

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

• Loss: 0.7279
• Accuracy: 0.5965

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cpu
• Datasets 3.3.0
• Tokenizers 0.21.0