---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-IpadicUnigram2
  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-IpadicUnigram2

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2725
- Accuracy: 0.7233

## 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: 14.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 1.7647        | 1.0   | 69473  | 1.6172          | 0.6646   |
| 1.6381        | 2.0   | 138946 | 1.4902          | 0.6853   |
| 1.5804        | 3.0   | 208419 | 1.4355          | 0.6951   |
| 1.5448        | 4.0   | 277892 | 1.4004          | 0.7008   |
| 1.52          | 5.0   | 347365 | 1.3740          | 0.7058   |
| 1.4963        | 6.0   | 416838 | 1.3564          | 0.7089   |
| 1.485         | 7.0   | 486311 | 1.3398          | 0.7113   |
| 1.4665        | 8.0   | 555784 | 1.3252          | 0.7138   |
| 1.454         | 9.0   | 625257 | 1.3145          | 0.7158   |
| 1.4447        | 10.0  | 694730 | 1.3027          | 0.7182   |
| 1.4341        | 11.0  | 764203 | 1.2949          | 0.7192   |
| 1.4266        | 12.0  | 833676 | 1.2861          | 0.7205   |
| 1.4191        | 13.0  | 903149 | 1.2764          | 0.7224   |
| 1.4118        | 14.0  | 972622 | 1.2725          | 0.7233   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.9.0
- Tokenizers 0.12.1