README.md

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