---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased-Hate_Offensive_or_Normal_Speech
  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-large-uncased-Hate_Offensive_or_Normal_Speech

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0610
- Accuracy: 0.9853
- Weighted f1: 0.9853
- Weighted recall: 0.9853
- Weighted precision: 0.9854
- Micro f1: 0.9853
- Micro recall: 0.9853
- Micro precision: 0.9853
- Macro f1: 0.9851
- Macro recall: 0.9850
- Macro precision: 0.9853

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Weighted recall | Weighted precision | Micro f1 | Micro recall | Micro precision | Macro f1 | Macro recall | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:|
| 0.2927        | 1.0   | 153  | 0.1163          | 0.9462   | 0.9469      | 0.9462          | 0.9512             | 0.9462   | 0.9462       | 0.9462          | 0.9429   | 0.9472       | 0.9427          |
| 0.066         | 2.0   | 306  | 0.1119          | 0.9739   | 0.9739      | 0.9739          | 0.9741             | 0.9739   | 0.9739       | 0.9739          | 0.9729   | 0.9742       | 0.9718          |
| 0.0267        | 3.0   | 459  | 0.0805          | 0.9821   | 0.9821      | 0.9821          | 0.9825             | 0.9821   | 0.9821       | 0.9821          | 0.9804   | 0.9815       | 0.9796          |
| 0.0209        | 4.0   | 612  | 0.0610          | 0.9853   | 0.9853      | 0.9853          | 0.9854             | 0.9853   | 0.9853       | 0.9853          | 0.9851   | 0.9850       | 0.9853          |
| 0.0097        | 5.0   | 765  | 0.0673          | 0.9837   | 0.9836      | 0.9837          | 0.9838             | 0.9837   | 0.9837       | 0.9837          | 0.9832   | 0.9833       | 0.9833          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3