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-multilabel-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-multilabel-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: 0.3230
- Accuracy: 0.8701

## 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: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 306   | 0.4850          | 0.7861   |
| 0.5279        | 2.0   | 612   | 0.4657          | 0.7881   |
| 0.5279        | 3.0   | 918   | 0.4495          | 0.7979   |
| 0.4707        | 4.0   | 1224  | 0.4361          | 0.8115   |
| 0.448         | 5.0   | 1530  | 0.4252          | 0.8242   |
| 0.448         | 6.0   | 1836  | 0.4169          | 0.8271   |
| 0.4321        | 7.0   | 2142  | 0.4098          | 0.8369   |
| 0.4321        | 8.0   | 2448  | 0.4037          | 0.8389   |
| 0.4208        | 9.0   | 2754  | 0.3989          | 0.8428   |
| 0.4129        | 10.0  | 3060  | 0.3942          | 0.8447   |
| 0.4129        | 11.0  | 3366  | 0.3905          | 0.8457   |
| 0.4058        | 12.0  | 3672  | 0.3865          | 0.8467   |
| 0.4058        | 13.0  | 3978  | 0.3833          | 0.8496   |
| 0.4041        | 14.0  | 4284  | 0.3802          | 0.8496   |
| 0.3992        | 15.0  | 4590  | 0.3774          | 0.8506   |
| 0.3992        | 16.0  | 4896  | 0.3749          | 0.8525   |
| 0.3922        | 17.0  | 5202  | 0.3726          | 0.8525   |
| 0.3936        | 18.0  | 5508  | 0.3701          | 0.8535   |
| 0.3936        | 19.0  | 5814  | 0.3679          | 0.8535   |
| 0.3893        | 20.0  | 6120  | 0.3666          | 0.8535   |
| 0.3893        | 21.0  | 6426  | 0.3640          | 0.8555   |
| 0.3871        | 22.0  | 6732  | 0.3626          | 0.8545   |
| 0.3856        | 23.0  | 7038  | 0.3607          | 0.8555   |
| 0.3856        | 24.0  | 7344  | 0.3591          | 0.8564   |
| 0.3836        | 25.0  | 7650  | 0.3572          | 0.8584   |
| 0.3836        | 26.0  | 7956  | 0.3561          | 0.8604   |
| 0.3801        | 27.0  | 8262  | 0.3543          | 0.8604   |
| 0.3794        | 28.0  | 8568  | 0.3530          | 0.8613   |
| 0.3794        | 29.0  | 8874  | 0.3517          | 0.8633   |
| 0.379         | 30.0  | 9180  | 0.3505          | 0.8633   |
| 0.379         | 31.0  | 9486  | 0.3494          | 0.8633   |
| 0.377         | 32.0  | 9792  | 0.3482          | 0.8623   |
| 0.3765        | 33.0  | 10098 | 0.3471          | 0.8662   |
| 0.3765        | 34.0  | 10404 | 0.3465          | 0.8652   |
| 0.3739        | 35.0  | 10710 | 0.3456          | 0.8613   |
| 0.3737        | 36.0  | 11016 | 0.3441          | 0.8662   |
| 0.3737        | 37.0  | 11322 | 0.3435          | 0.8662   |
| 0.3723        | 38.0  | 11628 | 0.3426          | 0.8662   |
| 0.3723        | 39.0  | 11934 | 0.3418          | 0.8652   |
| 0.3728        | 40.0  | 12240 | 0.3410          | 0.8652   |
| 0.3713        | 41.0  | 12546 | 0.3401          | 0.8633   |
| 0.3713        | 42.0  | 12852 | 0.3395          | 0.8662   |
| 0.3686        | 43.0  | 13158 | 0.3392          | 0.8662   |
| 0.3686        | 44.0  | 13464 | 0.3378          | 0.8643   |
| 0.3693        | 45.0  | 13770 | 0.3375          | 0.8662   |
| 0.3685        | 46.0  | 14076 | 0.3365          | 0.8643   |
| 0.3685        | 47.0  | 14382 | 0.3362          | 0.8643   |
| 0.3675        | 48.0  | 14688 | 0.3352          | 0.8633   |
| 0.3675        | 49.0  | 14994 | 0.3349          | 0.8643   |
| 0.3654        | 50.0  | 15300 | 0.3341          | 0.8652   |
| 0.3672        | 51.0  | 15606 | 0.3339          | 0.8672   |
| 0.3672        | 52.0  | 15912 | 0.3335          | 0.8682   |
| 0.3659        | 53.0  | 16218 | 0.3325          | 0.8643   |
| 0.3648        | 54.0  | 16524 | 0.3323          | 0.8662   |
| 0.3648        | 55.0  | 16830 | 0.3315          | 0.8643   |
| 0.3638        | 56.0  | 17136 | 0.3314          | 0.8643   |
| 0.3638        | 57.0  | 17442 | 0.3307          | 0.8662   |
| 0.3657        | 58.0  | 17748 | 0.3304          | 0.8662   |
| 0.3641        | 59.0  | 18054 | 0.3299          | 0.8662   |
| 0.3641        | 60.0  | 18360 | 0.3297          | 0.8672   |
| 0.3624        | 61.0  | 18666 | 0.3294          | 0.8672   |
| 0.3624        | 62.0  | 18972 | 0.3290          | 0.8662   |
| 0.3625        | 63.0  | 19278 | 0.3285          | 0.8662   |
| 0.3639        | 64.0  | 19584 | 0.3281          | 0.8662   |
| 0.3639        | 65.0  | 19890 | 0.3282          | 0.8682   |
| 0.3632        | 66.0  | 20196 | 0.3274          | 0.8652   |
| 0.3618        | 67.0  | 20502 | 0.3273          | 0.8682   |
| 0.3618        | 68.0  | 20808 | 0.3270          | 0.8672   |
| 0.3636        | 69.0  | 21114 | 0.3267          | 0.8672   |
| 0.3636        | 70.0  | 21420 | 0.3265          | 0.8662   |
| 0.3577        | 71.0  | 21726 | 0.3262          | 0.8682   |
| 0.3607        | 72.0  | 22032 | 0.3262          | 0.8682   |
| 0.3607        | 73.0  | 22338 | 0.3258          | 0.8682   |
| 0.3591        | 74.0  | 22644 | 0.3255          | 0.8662   |
| 0.3591        | 75.0  | 22950 | 0.3255          | 0.8691   |
| 0.3597        | 76.0  | 23256 | 0.3252          | 0.8691   |
| 0.3593        | 77.0  | 23562 | 0.3250          | 0.8691   |
| 0.3593        | 78.0  | 23868 | 0.3248          | 0.8682   |
| 0.3597        | 79.0  | 24174 | 0.3246          | 0.8682   |
| 0.3597        | 80.0  | 24480 | 0.3244          | 0.8672   |
| 0.3593        | 81.0  | 24786 | 0.3243          | 0.8672   |
| 0.3602        | 82.0  | 25092 | 0.3242          | 0.8682   |
| 0.3602        | 83.0  | 25398 | 0.3242          | 0.8672   |
| 0.3579        | 84.0  | 25704 | 0.3242          | 0.8711   |
| 0.3614        | 85.0  | 26010 | 0.3238          | 0.8672   |
| 0.3614        | 86.0  | 26316 | 0.3238          | 0.8711   |
| 0.359         | 87.0  | 26622 | 0.3237          | 0.8701   |
| 0.359         | 88.0  | 26928 | 0.3236          | 0.8682   |
| 0.3583        | 89.0  | 27234 | 0.3235          | 0.8682   |
| 0.3591        | 90.0  | 27540 | 0.3234          | 0.8682   |
| 0.3591        | 91.0  | 27846 | 0.3233          | 0.8691   |
| 0.3581        | 92.0  | 28152 | 0.3231          | 0.8672   |
| 0.3581        | 93.0  | 28458 | 0.3232          | 0.8701   |
| 0.3579        | 94.0  | 28764 | 0.3231          | 0.8691   |
| 0.3584        | 95.0  | 29070 | 0.3231          | 0.8701   |
| 0.3584        | 96.0  | 29376 | 0.3230          | 0.8701   |
| 0.356         | 97.0  | 29682 | 0.3230          | 0.8691   |
| 0.356         | 98.0  | 29988 | 0.3230          | 0.8691   |
| 0.3604        | 99.0  | 30294 | 0.3230          | 0.8701   |
| 0.3607        | 100.0 | 30600 | 0.3230          | 0.8701   |


### Framework versions

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