---
license: apache-2.0
base_model: line-corporation/line-distilbert-base-japanese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: factual-consistency-classification-ja
  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. -->

# factual-consistency-classification-ja

This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8034
- Accuracy: 0.6230

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 306  | 1.0539          | 0.2891   |
| 1.0502        | 2.0   | 612  | 1.0074          | 0.3203   |
| 1.0502        | 3.0   | 918  | 0.9738          | 0.3711   |
| 0.9895        | 4.0   | 1224 | 0.9452          | 0.4453   |
| 0.9483        | 5.0   | 1530 | 0.9245          | 0.4766   |
| 0.9483        | 6.0   | 1836 | 0.9041          | 0.5566   |
| 0.918         | 7.0   | 2142 | 0.8945          | 0.5117   |
| 0.918         | 8.0   | 2448 | 0.8853          | 0.5      |
| 0.9002        | 9.0   | 2754 | 0.8786          | 0.4922   |
| 0.884         | 10.0  | 3060 | 0.8658          | 0.5352   |
| 0.884         | 11.0  | 3366 | 0.8614          | 0.5176   |
| 0.8697        | 12.0  | 3672 | 0.8467          | 0.5938   |
| 0.8697        | 13.0  | 3978 | 0.8429          | 0.5801   |
| 0.8648        | 14.0  | 4284 | 0.8386          | 0.5703   |
| 0.8571        | 15.0  | 4590 | 0.8311          | 0.5996   |
| 0.8571        | 16.0  | 4896 | 0.8289          | 0.5879   |
| 0.8478        | 17.0  | 5202 | 0.8285          | 0.5762   |
| 0.8468        | 18.0  | 5508 | 0.8193          | 0.6152   |
| 0.8468        | 19.0  | 5814 | 0.8192          | 0.5957   |
| 0.8439        | 20.0  | 6120 | 0.8165          | 0.5996   |
| 0.8439        | 21.0  | 6426 | 0.8157          | 0.5918   |
| 0.8396        | 22.0  | 6732 | 0.8120          | 0.6055   |
| 0.8354        | 23.0  | 7038 | 0.8103          | 0.6055   |
| 0.8354        | 24.0  | 7344 | 0.8091          | 0.6035   |
| 0.8362        | 25.0  | 7650 | 0.8055          | 0.6152   |
| 0.8362        | 26.0  | 7956 | 0.8055          | 0.6074   |
| 0.8334        | 27.0  | 8262 | 0.8045          | 0.6211   |
| 0.8325        | 28.0  | 8568 | 0.8037          | 0.6191   |
| 0.8325        | 29.0  | 8874 | 0.8034          | 0.6230   |
| 0.833         | 30.0  | 9180 | 0.8034          | 0.6230   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0