---
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: 0.7285
- Accuracy: 0.8132
- Precision: 0.8131
- Recall: 0.8173
- F1 Macro: 0.8123
- F1 Micro: 0.8132
- F1 Weighted: 0.8094

## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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  | 0.6284          | 0.7675   | 0.7662    | 0.7721 | 0.7681   | 0.7675   | 0.7654      |
| No log        | 2.0   | 250  | 0.5576          | 0.7820   | 0.7826    | 0.7799 | 0.7796   | 0.7820   | 0.7803      |
| No log        | 3.0   | 375  | 0.5405          | 0.8001   | 0.8122    | 0.8077 | 0.8026   | 0.8001   | 0.7943      |
| 0.5338        | 4.0   | 500  | 0.5853          | 0.8172   | 0.8140    | 0.8120 | 0.8124   | 0.8172   | 0.8161      |
| 0.5338        | 5.0   | 625  | 0.6476          | 0.8157   | 0.8143    | 0.8098 | 0.8118   | 0.8157   | 0.8148      |
| 0.5338        | 6.0   | 750  | 0.6607          | 0.8122   | 0.8137    | 0.8173 | 0.8120   | 0.8122   | 0.8082      |
| 0.5338        | 7.0   | 875  | 0.7285          | 0.8132   | 0.8131    | 0.8173 | 0.8123   | 0.8132   | 0.8094      |


### Framework versions

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