---
license: apache-2.0
base_model: line-corporation/line-distilbert-base-japanese
tags:
- generated_from_trainer
model-index:
- name: toxicity-score-multi-classification
  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. -->

# toxicity-score-multi-classification

This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on a [Japanese toxicity dataset](https://github.com/inspection-ai/japanese-toxic-dataset/tree/main).
It achieves the following results on the evaluation set:
- Loss: 0.2649
- Roc Auc: 0.7992

## 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: 8.133692392125703e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 20   | 0.6213          | 0.5148  |
| No log        | 2.0   | 40   | 0.4762          | 0.4616  |
| No log        | 3.0   | 60   | 0.3754          | 0.5830  |
| No log        | 4.0   | 80   | 0.3314          | 0.5706  |
| No log        | 5.0   | 100  | 0.3140          | 0.5740  |
| No log        | 6.0   | 120  | 0.3067          | 0.6238  |
| No log        | 7.0   | 140  | 0.3010          | 0.6645  |
| No log        | 8.0   | 160  | 0.2975          | 0.7177  |
| No log        | 9.0   | 180  | 0.2949          | 0.7392  |
| No log        | 10.0  | 200  | 0.2892          | 0.7731  |
| No log        | 11.0  | 220  | 0.2828          | 0.7954  |
| No log        | 12.0  | 240  | 0.2827          | 0.7932  |
| No log        | 13.0  | 260  | 0.2756          | 0.7984  |
| No log        | 14.0  | 280  | 0.2715          | 0.8052  |
| No log        | 15.0  | 300  | 0.2733          | 0.8100  |
| No log        | 16.0  | 320  | 0.2754          | 0.8142  |
| No log        | 17.0  | 340  | 0.2668          | 0.8130  |
| No log        | 18.0  | 360  | 0.2642          | 0.8138  |
| No log        | 19.0  | 380  | 0.2639          | 0.8117  |
| No log        | 20.0  | 400  | 0.2659          | 0.8052  |
| No log        | 21.0  | 420  | 0.2646          | 0.8082  |
| No log        | 22.0  | 440  | 0.2643          | 0.8039  |
| No log        | 23.0  | 460  | 0.2646          | 0.8022  |
| No log        | 24.0  | 480  | 0.2644          | 0.8044  |
| 0.2305        | 25.0  | 500  | 0.2639          | 0.8035  |
| 0.2305        | 26.0  | 520  | 0.2639          | 0.8027  |
| 0.2305        | 27.0  | 540  | 0.2647          | 0.8001  |
| 0.2305        | 28.0  | 560  | 0.2643          | 0.8005  |
| 0.2305        | 29.0  | 580  | 0.2649          | 0.8001  |
| 0.2305        | 30.0  | 600  | 0.2649          | 0.7992  |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.14.0