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---
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
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