---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-base-uncased-finetuned-toxic-comment-detection-ws23
  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-base-uncased-finetuned-toxic-comment-detection-ws23

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1991
- Accuracy: 0.945
- Precision: 0.7273
- Recall: 0.7619
- F1: 0.7442

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4756        | 1.0   | 50   | 0.2585          | 0.91     | 1.0       | 0.1429 | 0.25   |
| 0.1843        | 2.0   | 100  | 0.1417          | 0.93     | 0.7333    | 0.5238 | 0.6111 |
| 0.1014        | 3.0   | 150  | 0.2207          | 0.935    | 0.9       | 0.4286 | 0.5806 |
| 0.0481        | 4.0   | 200  | 0.1991          | 0.945    | 0.7273    | 0.7619 | 0.7442 |
| 0.0105        | 5.0   | 250  | 0.2082          | 0.945    | 0.75      | 0.7143 | 0.7317 |
| 0.0028        | 6.0   | 300  | 0.2249          | 0.945    | 0.75      | 0.7143 | 0.7317 |
| 0.0017        | 7.0   | 350  | 0.2379          | 0.945    | 0.7273    | 0.7619 | 0.7442 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0