---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT_Offensive_English_Twitter
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# BERT_Offensive_English_Twitter

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2731
- Macro F1: 0.8890
- Micro F1: 0.8954
- Accuracy: 0.8954

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Macro F1 | Micro F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|
| 0.3321        | 1.0   | 4036  | 0.6479          | 0.5302   | 0.5589   | 0.5589   |
| 0.4337        | 2.0   | 8073  | 0.3772          | 0.8346   | 0.8524   | 0.8524   |
| 0.2945        | 3.0   | 12109 | 0.3232          | 0.8753   | 0.8843   | 0.8843   |
| 0.243         | 4.0   | 16144 | 0.2731          | 0.8890   | 0.8954   | 0.8954   |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.1+cu118
- Datasets 2.9.0
- Tokenizers 0.13.3