---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-ipadic_bpe
  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. -->

# bert-small-ipadic_bpe

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6777
- Accuracy: 0.6519

## 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: 256
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 768
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 14
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.2548        | 1.0   | 69473  | 2.1163          | 0.5882   |
| 2.0904        | 2.0   | 138946 | 1.9562          | 0.6101   |
| 2.0203        | 3.0   | 208419 | 1.8848          | 0.6208   |
| 1.978         | 4.0   | 277892 | 1.8408          | 0.6272   |
| 1.937         | 5.0   | 347365 | 1.8080          | 0.6320   |
| 1.9152        | 6.0   | 416838 | 1.7818          | 0.6361   |
| 1.8982        | 7.0   | 486311 | 1.7575          | 0.6395   |
| 1.8808        | 8.0   | 555784 | 1.7413          | 0.6421   |
| 1.8684        | 9.0   | 625257 | 1.7282          | 0.6440   |
| 1.8517        | 10.0  | 694730 | 1.7140          | 0.6464   |
| 1.8353        | 11.0  | 764203 | 1.7022          | 0.6481   |
| 1.8245        | 12.0  | 833676 | 1.6877          | 0.6504   |
| 1.8191        | 13.0  | 903149 | 1.6829          | 0.6515   |
| 1.8122        | 14.0  | 972622 | 1.6777          | 0.6519   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.2.2
- Tokenizers 0.12.1