|
--- |
|
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 |
