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: output
  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. -->

# output

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: 0.3471
- Accuracy: 0.8672

## 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: 0.0001
- 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  | 0.3968          | 0.8594   |
| 0.4221        | 2.0   | 612  | 0.3889          | 0.8594   |
| 0.4221        | 3.0   | 918  | 0.3814          | 0.8594   |
| 0.4026        | 4.0   | 1224 | 0.3775          | 0.8594   |
| 0.396         | 5.0   | 1530 | 0.3724          | 0.8594   |
| 0.396         | 6.0   | 1836 | 0.3707          | 0.8594   |
| 0.392         | 7.0   | 2142 | 0.3721          | 0.8594   |
| 0.392         | 8.0   | 2448 | 0.3653          | 0.8594   |
| 0.3898        | 9.0   | 2754 | 0.3765          | 0.8613   |
| 0.3835        | 10.0  | 3060 | 0.3572          | 0.8594   |
| 0.3835        | 11.0  | 3366 | 0.3664          | 0.8613   |
| 0.3869        | 12.0  | 3672 | 0.3568          | 0.8613   |
| 0.3869        | 13.0  | 3978 | 0.3583          | 0.8613   |
| 0.3825        | 14.0  | 4284 | 0.3526          | 0.8613   |
| 0.3813        | 15.0  | 4590 | 0.3581          | 0.8613   |
| 0.3813        | 16.0  | 4896 | 0.3553          | 0.8613   |
| 0.3759        | 17.0  | 5202 | 0.3504          | 0.8613   |
| 0.3788        | 18.0  | 5508 | 0.3490          | 0.8613   |
| 0.3788        | 19.0  | 5814 | 0.3520          | 0.8613   |
| 0.3754        | 20.0  | 6120 | 0.3450          | 0.8613   |
| 0.3754        | 21.0  | 6426 | 0.3494          | 0.8633   |
| 0.3748        | 22.0  | 6732 | 0.3491          | 0.8633   |
| 0.3775        | 23.0  | 7038 | 0.3499          | 0.8633   |
| 0.3775        | 24.0  | 7344 | 0.3494          | 0.8633   |
| 0.3748        | 25.0  | 7650 | 0.3504          | 0.8672   |
| 0.3748        | 26.0  | 7956 | 0.3495          | 0.8672   |
| 0.3701        | 27.0  | 8262 | 0.3454          | 0.8633   |
| 0.3712        | 28.0  | 8568 | 0.3472          | 0.8633   |
| 0.3712        | 29.0  | 8874 | 0.3478          | 0.8672   |
| 0.3751        | 30.0  | 9180 | 0.3471          | 0.8672   |


### Framework versions

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