---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-hate-offensive-normal-speech-lr-2e-05
  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. -->

# roberta-large-hate-offensive-normal-speech-lr-2e-05

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0293
- Accuracy: 0.9837
- Weighted f1: 0.9837
- Weighted recall: 0.9837
- Weighted precision: 0.9839
- Micro f1: 0.9837
- Micro recall: 0.9837
- Micro precision: 0.9837
- Macro f1: 0.9832
- Macro recall: 0.9821
- Macro precision: 0.9845

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:|
| 0.5253        | 1.0   | 153  | 0.1270          | 0.9642   | 0.9647      | 0.9642          | 0.9681             | 0.9642   | 0.9642       | 0.9642          | 0.9633   | 0.9662       | 0.9633          |
| 0.0921        | 2.0   | 306  | 0.0878          | 0.9805   | 0.9805      | 0.9805          | 0.9807             | 0.9805   | 0.9805       | 0.9805          | 0.9803   | 0.9791       | 0.9818          |
| 0.0413        | 3.0   | 459  | 0.0590          | 0.9870   | 0.9870      | 0.9870          | 0.9875             | 0.9870   | 0.9870       | 0.9870          | 0.9860   | 0.9869       | 0.9857          |
| 0.0261        | 4.0   | 612  | 0.0523          | 0.9902   | 0.9902      | 0.9902          | 0.9904             | 0.9902   | 0.9902       | 0.9902          | 0.9896   | 0.9896       | 0.9900          |
| 0.012         | 5.0   | 765  | 0.0293          | 0.9837   | 0.9837      | 0.9837          | 0.9839             | 0.9837   | 0.9837       | 0.9837          | 0.9832   | 0.9821       | 0.9845          |


### Framework versions

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