transformers pytorch distilbert generated_from_trainer base_model:line-corporation/line-distilbert-base-japanese license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: line-corporation/line-distilbert-base-japanese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: factual-consistency-classification-with-prompt-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-with-prompt-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: 0.6642
- Accuracy: 0.6738

## 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: 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: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 306   | 1.0023          | 0.3223   |
| 1.0128        | 2.0   | 612   | 0.9182          | 0.5742   |
| 1.0128        | 3.0   | 918   | 0.8847          | 0.5547   |
| 0.9226        | 4.0   | 1224  | 0.8569          | 0.5859   |
| 0.8815        | 5.0   | 1530  | 0.8329          | 0.6191   |
| 0.8815        | 6.0   | 1836  | 0.8287          | 0.5840   |
| 0.8633        | 7.0   | 2142  | 0.8160          | 0.5723   |
| 0.8633        | 8.0   | 2448  | 0.8210          | 0.5098   |
| 0.8525        | 9.0   | 2754  | 0.8171          | 0.5156   |
| 0.8418        | 10.0  | 3060  | 0.7850          | 0.5840   |
| 0.8418        | 11.0  | 3366  | 0.7771          | 0.6035   |
| 0.8323        | 12.0  | 3672  | 0.7652          | 0.6797   |
| 0.8323        | 13.0  | 3978  | 0.7655          | 0.6055   |
| 0.8292        | 14.0  | 4284  | 0.7556          | 0.6719   |
| 0.8233        | 15.0  | 4590  | 0.7578          | 0.6660   |
| 0.8233        | 16.0  | 4896  | 0.7497          | 0.6270   |
| 0.8173        | 17.0  | 5202  | 0.7472          | 0.6484   |
| 0.8122        | 18.0  | 5508  | 0.7334          | 0.7090   |
| 0.8122        | 19.0  | 5814  | 0.7468          | 0.6016   |
| 0.8165        | 20.0  | 6120  | 0.7248          | 0.7363   |
| 0.8165        | 21.0  | 6426  | 0.7324          | 0.6484   |
| 0.8048        | 22.0  | 6732  | 0.7261          | 0.6836   |
| 0.8033        | 23.0  | 7038  | 0.7187          | 0.7031   |
| 0.8033        | 24.0  | 7344  | 0.7205          | 0.6816   |
| 0.8011        | 25.0  | 7650  | 0.7307          | 0.6133   |
| 0.8011        | 26.0  | 7956  | 0.7220          | 0.6680   |
| 0.7979        | 27.0  | 8262  | 0.7175          | 0.6660   |
| 0.7963        | 28.0  | 8568  | 0.7205          | 0.6367   |
| 0.7963        | 29.0  | 8874  | 0.7139          | 0.6719   |
| 0.7942        | 30.0  | 9180  | 0.7078          | 0.6875   |
| 0.7942        | 31.0  | 9486  | 0.7094          | 0.6602   |
| 0.7878        | 32.0  | 9792  | 0.6992          | 0.7148   |
| 0.7891        | 33.0  | 10098 | 0.7041          | 0.6680   |
| 0.7891        | 34.0  | 10404 | 0.6968          | 0.6973   |
| 0.7869        | 35.0  | 10710 | 0.7047          | 0.6465   |
| 0.7874        | 36.0  | 11016 | 0.6962          | 0.6934   |
| 0.7874        | 37.0  | 11322 | 0.7026          | 0.6523   |
| 0.7817        | 38.0  | 11628 | 0.7103          | 0.625    |
| 0.7817        | 39.0  | 11934 | 0.6917          | 0.6914   |
| 0.7843        | 40.0  | 12240 | 0.6957          | 0.6680   |
| 0.7805        | 41.0  | 12546 | 0.7016          | 0.6484   |
| 0.7805        | 42.0  | 12852 | 0.6955          | 0.6582   |
| 0.7777        | 43.0  | 13158 | 0.7004          | 0.6387   |
| 0.7777        | 44.0  | 13464 | 0.6855          | 0.6895   |
| 0.7783        | 45.0  | 13770 | 0.6835          | 0.6895   |
| 0.7766        | 46.0  | 14076 | 0.6886          | 0.6641   |
| 0.7766        | 47.0  | 14382 | 0.6969          | 0.6309   |
| 0.7796        | 48.0  | 14688 | 0.6873          | 0.6738   |
| 0.7796        | 49.0  | 14994 | 0.6796          | 0.6953   |
| 0.77          | 50.0  | 15300 | 0.6908          | 0.6543   |
| 0.7768        | 51.0  | 15606 | 0.6900          | 0.6367   |
| 0.7768        | 52.0  | 15912 | 0.6855          | 0.6680   |
| 0.7698        | 53.0  | 16218 | 0.6905          | 0.6504   |
| 0.7686        | 54.0  | 16524 | 0.6783          | 0.6816   |
| 0.7686        | 55.0  | 16830 | 0.6807          | 0.6777   |
| 0.7712        | 56.0  | 17136 | 0.6767          | 0.6797   |
| 0.7712        | 57.0  | 17442 | 0.6966          | 0.6152   |
| 0.7692        | 58.0  | 17748 | 0.6812          | 0.6660   |
| 0.7677        | 59.0  | 18054 | 0.6762          | 0.6777   |
| 0.7677        | 60.0  | 18360 | 0.6697          | 0.7090   |
| 0.761         | 61.0  | 18666 | 0.6833          | 0.6445   |
| 0.761         | 62.0  | 18972 | 0.6753          | 0.6777   |
| 0.7676        | 63.0  | 19278 | 0.6757          | 0.6699   |
| 0.7627        | 64.0  | 19584 | 0.6874          | 0.6426   |
| 0.7627        | 65.0  | 19890 | 0.6704          | 0.6836   |
| 0.7672        | 66.0  | 20196 | 0.6685          | 0.6934   |
| 0.7638        | 67.0  | 20502 | 0.6645          | 0.7090   |
| 0.7638        | 68.0  | 20808 | 0.6718          | 0.6797   |
| 0.765         | 69.0  | 21114 | 0.6658          | 0.6934   |
| 0.765         | 70.0  | 21420 | 0.6670          | 0.6895   |
| 0.7593        | 71.0  | 21726 | 0.6735          | 0.6719   |
| 0.7634        | 72.0  | 22032 | 0.6765          | 0.6406   |
| 0.7634        | 73.0  | 22338 | 0.6722          | 0.6641   |
| 0.754         | 74.0  | 22644 | 0.6664          | 0.6855   |
| 0.754         | 75.0  | 22950 | 0.6659          | 0.6895   |
| 0.7619        | 76.0  | 23256 | 0.6700          | 0.6621   |
| 0.7583        | 77.0  | 23562 | 0.6664          | 0.6797   |
| 0.7583        | 78.0  | 23868 | 0.6650          | 0.6836   |
| 0.7556        | 79.0  | 24174 | 0.6615          | 0.6973   |
| 0.7556        | 80.0  | 24480 | 0.6625          | 0.6934   |
| 0.7571        | 81.0  | 24786 | 0.6704          | 0.6582   |
| 0.7549        | 82.0  | 25092 | 0.6677          | 0.6719   |
| 0.7549        | 83.0  | 25398 | 0.6670          | 0.6699   |
| 0.7542        | 84.0  | 25704 | 0.6617          | 0.6875   |
| 0.756         | 85.0  | 26010 | 0.6638          | 0.6758   |
| 0.756         | 86.0  | 26316 | 0.6697          | 0.6562   |
| 0.7513        | 87.0  | 26622 | 0.6647          | 0.6738   |
| 0.7513        | 88.0  | 26928 | 0.6734          | 0.6445   |
| 0.7548        | 89.0  | 27234 | 0.6637          | 0.6836   |
| 0.7565        | 90.0  | 27540 | 0.6665          | 0.6719   |
| 0.7565        | 91.0  | 27846 | 0.6708          | 0.6504   |
| 0.7488        | 92.0  | 28152 | 0.6603          | 0.6895   |
| 0.7488        | 93.0  | 28458 | 0.6671          | 0.6582   |
| 0.7545        | 94.0  | 28764 | 0.6655          | 0.6699   |
| 0.7509        | 95.0  | 29070 | 0.6636          | 0.6777   |
| 0.7509        | 96.0  | 29376 | 0.6620          | 0.6816   |
| 0.7546        | 97.0  | 29682 | 0.6653          | 0.6719   |
| 0.7546        | 98.0  | 29988 | 0.6636          | 0.6738   |
| 0.7521        | 99.0  | 30294 | 0.6636          | 0.6758   |
| 0.755         | 100.0 | 30600 | 0.6642          | 0.6738   |


### Framework versions

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