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---
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 |