---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: ibert-roberta-base-Abusive_Or_Threatening_Speech
  results: []
---

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# ibert-roberta-base-Abusive_Or_Threatening_Speech

This model is a fine-tuned version of [kssteven/ibert-roberta-base](https://huggingface.co/kssteven/ibert-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0802
- Accuracy: 0.9741
- F1: 0.7773
- Recall: 0.8610
- Precision: 0.7084

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0771        | 1.0   | 1828 | 0.0802          | 0.9741   | 0.7773 | 0.8610 | 0.7084    |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.8.0
- Tokenizers 0.12.1