---
base_model: readerbench/RoBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: ro-offense-01
  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. -->

# ro-offense-01

This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8411
- Accuracy: 0.8232
- Precision: 0.8235
- Recall: 0.8210
- F1 Macro: 0.8207
- F1 Micro: 0.8232
- F1 Weighted: 0.8210

## 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: 4e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Macro | F1 Micro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:-----------:|
| No log        | 1.0   | 125  | 0.7789          | 0.7037   | 0.6825    | 0.7000 | 0.6873   | 0.7037   | 0.7132      |
| No log        | 2.0   | 250  | 0.5170          | 0.8006   | 0.8066    | 0.8016 | 0.7986   | 0.8006   | 0.7971      |
| No log        | 3.0   | 375  | 0.5139          | 0.8096   | 0.8168    | 0.8237 | 0.8120   | 0.8096   | 0.8047      |
| 0.6074        | 4.0   | 500  | 0.6180          | 0.8247   | 0.8251    | 0.8187 | 0.8210   | 0.8247   | 0.8233      |
| 0.6074        | 5.0   | 625  | 0.7311          | 0.8096   | 0.8071    | 0.8085 | 0.8064   | 0.8096   | 0.8071      |
| 0.6074        | 6.0   | 750  | 0.8365          | 0.8101   | 0.8117    | 0.8191 | 0.8105   | 0.8101   | 0.8051      |
| 0.6074        | 7.0   | 875  | 0.8411          | 0.8232   | 0.8235    | 0.8210 | 0.8207   | 0.8232   | 0.8210      |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3