metadata
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: []
Bert-finetuned-toxic-comment-classification-v2
This model is a fine-tuned version of 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