---
license: apache-2.0
base_model: bert-base-uncased
tags:
- Language
- toxic-comment
- Bert
- PyTorch
- Trainer
- F1Score
- HuggingFaceHub
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: Bert-finetuned-toxic-comment-classification-v2
  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-finetuned-toxic-comment-classification-v2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the toxic-comment-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1438
- Accuracy: 0.965
- Recall: 0.7143
- Precision: 0.9375
- F1: 0.8108

## 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: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2792        | 1.0   | 100  | 0.2226          | 0.96     | 0.6190 | 1.0       | 0.7647 |
| 0.154         | 2.0   | 200  | 0.1438          | 0.965    | 0.7143 | 0.9375    | 0.8108 |
| 0.0488        | 3.0   | 300  | 0.2012          | 0.965    | 0.9524 | 0.7692    | 0.8511 |
| 0.015         | 4.0   | 400  | 0.2588          | 0.955    | 0.7143 | 0.8333    | 0.7692 |
| 0.0035        | 5.0   | 500  | 0.2444          | 0.965    | 0.7619 | 0.8889    | 0.8205 |
| 0.0001        | 6.0   | 600  | 0.2524          | 0.965    | 0.7619 | 0.8889    | 0.8205 |
| 0.0001        | 7.0   | 700  | 0.2580          | 0.965    | 0.7619 | 0.8889    | 0.8205 |
| 0.0001        | 8.0   | 800  | 0.2621          | 0.965    | 0.7619 | 0.8889    | 0.8205 |
| 0.0001        | 9.0   | 900  | 0.2646          | 0.965    | 0.7619 | 0.8889    | 0.8205 |
| 0.0001        | 10.0  | 1000 | 0.2654          | 0.965    | 0.7619 | 0.8889    | 0.8205 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1