---
license: cc-by-sa-4.0
base_model: cl-tohoku/bert-base-japanese
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-japanese-ghost_rate-weighted
  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-base-japanese-ghost_rate-weighted

This model is a fine-tuned version of [cl-tohoku/bert-base-japanese](https://huggingface.co/cl-tohoku/bert-base-japanese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7735
- Accuracy: 0.4195
- F1: 0.4186

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.9977 | 220  | 1.5524          | 0.3651   | 0.3644 |
| No log        | 2.0    | 441  | 1.5018          | 0.3781   | 0.3761 |
| 1.5438        | 2.9977 | 661  | 1.5367          | 0.3934   | 0.3832 |
| 1.5438        | 4.0    | 882  | 1.5724          | 0.4019   | 0.4042 |
| 1.1647        | 4.9977 | 1102 | 1.6488          | 0.4093   | 0.4115 |
| 1.1647        | 6.0    | 1323 | 1.7250          | 0.4138   | 0.4176 |
| 0.8864        | 6.9977 | 1543 | 1.7735          | 0.4195   | 0.4186 |
| 0.8864        | 8.0    | 1764 | 1.8372          | 0.4138   | 0.4161 |
| 0.8864        | 8.9977 | 1984 | 1.8975          | 0.4150   | 0.4133 |
| 0.6978        | 9.9773 | 2200 | 1.8925          | 0.4127   | 0.4146 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1