---
license: cc-by-sa-4.0
base_model: cl-tohoku/bert-base-japanese-whole-word-masking
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_review_model
  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. -->

# my_review_model

This model is a fine-tuned version of [cl-tohoku/bert-base-japanese-whole-word-masking](https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4346
- Accuracy: 0.9332

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2084        | 1.0   | 678  | 0.2145          | 0.9363   |
| 0.1852        | 2.0   | 1356 | 0.2198          | 0.9384   |
| 0.0955        | 3.0   | 2034 | 0.2944          | 0.9362   |
| 0.0469        | 4.0   | 2712 | 0.3892          | 0.9359   |
| 0.0318        | 5.0   | 3390 | 0.4346          | 0.9332   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0