---
license: cc-by-sa-4.0
base_model: tohoku-nlp/bert-base-japanese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gigazine-title-classification
  results: []
pipeline_tag: text-classification
---

<!-- 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. -->

# gigazine-title-classification

This model is a fine-tuned version of [tohoku-nlp/bert-base-japanese](https://huggingface.co/tohoku-nlp/bert-base-japanese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4894
- Accuracy: 0.617

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5588        | 0.768 | 3    | 1.5196          | 0.602    |
| 0.3835        | 1.792 | 7    | 1.4909          | 0.61     |
| 0.2563        | 2.304 | 9    | 1.4894          | 0.617    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1