---
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: []
---

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# bert-based_uncased-finetuned-binary_hate_speech

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/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