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: 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: 0.7280701754385965
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: 0.5418
- Accuracy: 0.7281
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
Training results
Framework versions
- Transformers 4.44.2
- Pytorch 2.7.1+cu118
- Datasets 2.15.0
- Tokenizers 0.19.1