---
license: mit
tags:
- question-answering
- generated_from_trainer
model-index:
- name: roberta_qa_japanese
  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. -->

# roberta_qa_japanese

This model is a fine-tuned version of [rinna/japanese-roberta-base](https://huggingface.co/rinna/japanese-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0516

## 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: 7e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1293        | 0.13  | 150  | 1.0311          |
| 1.1965        | 0.26  | 300  | 0.6723          |
| 1.022         | 0.39  | 450  | 0.4838          |
| 0.9594        | 0.53  | 600  | 0.5174          |
| 0.9187        | 0.66  | 750  | 0.4671          |
| 0.8229        | 0.79  | 900  | 0.4650          |
| 0.71          | 0.92  | 1050 | 0.2648          |
| 0.5436        | 1.05  | 1200 | 0.2665          |
| 0.5045        | 1.19  | 1350 | 0.2686          |
| 0.5025        | 1.32  | 1500 | 0.2082          |
| 0.5213        | 1.45  | 1650 | 0.1715          |
| 0.4648        | 1.58  | 1800 | 0.1563          |
| 0.4698        | 1.71  | 1950 | 0.1488          |
| 0.4823        | 1.84  | 2100 | 0.1050          |
| 0.4482        | 1.97  | 2250 | 0.0821          |
| 0.2755        | 2.11  | 2400 | 0.0898          |
| 0.2834        | 2.24  | 2550 | 0.0964          |
| 0.2525        | 2.37  | 2700 | 0.0533          |
| 0.2606        | 2.5   | 2850 | 0.0561          |
| 0.2467        | 2.63  | 3000 | 0.0601          |
| 0.2799        | 2.77  | 3150 | 0.0562          |
| 0.2497        | 2.9   | 3300 | 0.0516          |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1