README.md

metadata

license: mit
base_model: lucasresck/bert-base-cased-ag-news
tags:
  - generated_from_trainer
datasets:
  - ag_news
model-index:
  - name: bert-based_uncased-finetuned-binary_hate_speech
    results: []

bert-based_uncased-finetuned-binary_hate_speech

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

• eval_loss: 0.3032
• eval_accuracy: 0.9426
• eval_f1: 0.9426
• eval_precision: 0.9428
• eval_recall: 0.9426
• eval_runtime: 12.9777
• eval_samples_per_second: 585.618
• eval_steps_per_second: 18.339
• epoch: 2.0
• step: 7500

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Framework versions

• Transformers 4.34.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1