---
license: apache-2.0
base_model: cl-tohoku/bert-base-japanese-v3
tags:
- generated_from_trainer
model-index:
- name: isekai-bert-v1
  results: []
language:
- ja
library_name: transformers
widget:
- text: "異世界に[MASK]する"
  example_title: "例1"
- text: "[MASK]者ギルドへ向かう"
  example_title: "例2"
- text: "あの美少女は俺の[MASK]である"
  example_title: "例3"
---

<!-- 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. -->

# isekai-bert-v1

This model is a fine-tuned version of [cl-tohoku/bert-base-japanese-v3](https://huggingface.co/cl-tohoku/bert-base-japanese-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9164

## 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: 0.0005
- 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: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.9144        | 0.06  | 1000  | 2.6322          |
| 3.0793        | 0.13  | 2000  | 2.7752          |
| 3.0591        | 0.19  | 3000  | 2.8336          |
| 2.972         | 0.26  | 4000  | 2.9084          |
| 2.9967        | 0.32  | 5000  | 2.8845          |
| 2.9489        | 0.38  | 6000  | 2.7112          |
| 2.8639        | 0.45  | 7000  | 2.7209          |
| 2.8355        | 0.51  | 8000  | 2.6684          |
| 2.8162        | 0.58  | 9000  | 2.6209          |
| 2.7648        | 0.64  | 10000 | 2.5749          |
| 2.6663        | 0.7   | 11000 | 2.5231          |
| 2.6451        | 0.77  | 12000 | 2.4754          |
| 2.6041        | 0.83  | 13000 | 2.4279          |
| 2.5306        | 0.9   | 14000 | 2.3829          |
| 2.4765        | 0.96  | 15000 | 2.3137          |
| 2.3899        | 1.02  | 16000 | 2.3052          |
| 2.3681        | 1.09  | 17000 | 2.2123          |
| 2.2821        | 1.15  | 18000 | 2.1934          |
| 2.2288        | 1.22  | 19000 | 2.1399          |
| 2.1858        | 1.28  | 20000 | 2.0922          |
| 2.1964        | 1.34  | 21000 | 2.0689          |
| 2.1419        | 1.41  | 22000 | 2.0357          |
| 2.1011        | 1.47  | 23000 | 2.0327          |
| 2.039         | 1.54  | 24000 | 1.9853          |
| 2.0284        | 1.6   | 25000 | 1.9778          |
| 2.0253        | 1.66  | 26000 | 1.9869          |
| 2.0292        | 1.73  | 27000 | 1.9494          |
| 2.0016        | 1.79  | 28000 | 1.9158          |
| 2.0387        | 1.86  | 29000 | 1.9778          |
| 1.9679        | 1.92  | 30000 | 1.9171          |
| 2.0441        | 1.98  | 31000 | 1.9164          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0