File size: 2,511 Bytes
a75f770 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
---
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
|