matheusrp41/bert-hate-speech-test

1---2library_name: transformers3license: apache-2.04base_model: bert-base-uncased5tags:6- generated_from_trainer7metrics:8- accuracy9model-index:10- name: bert-hate-speech-test11  results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# bert-hate-speech-test18 19This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.20It achieves the following results on the evaluation set:21- Loss: 0.629122- Accuracy: 0.719323 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- learning_rate: 5e-0542- train_batch_size: 843- eval_batch_size: 844- seed: 4245- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments46- lr_scheduler_type: linear47- num_epochs: 348 49### Training results50 51| Training Loss | Epoch | Step | Validation Loss | Accuracy |52|:-------------:|:-----:|:----:|:---------------:|:--------:|53| 0.6593        | 1.0   | 57   | 0.6316          | 0.6667   |54| 0.6008        | 2.0   | 114  | 0.6574          | 0.6667   |55| 0.4936        | 3.0   | 171  | 0.6291          | 0.7193   |56 57 58### Framework versions59 60- Transformers 5.16.161- Pytorch 2.11.0+cpu62- Datasets 4.0.063- Tokenizers 0.23.164