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

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: 1.1279
- Accuracy: 0.7455

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 1.5872        | 1.0   | 69473  | 1.4531          | 0.6867   |
| 1.4695        | 2.0   | 138946 | 1.3340          | 0.7073   |
| 1.4136        | 3.0   | 208419 | 1.2793          | 0.7173   |
| 1.3779        | 4.0   | 277892 | 1.2490          | 0.7227   |
| 1.3546        | 5.0   | 347365 | 1.2227          | 0.7277   |
| 1.3353        | 6.0   | 416838 | 1.2070          | 0.7307   |
| 1.3182        | 7.0   | 486311 | 1.1895          | 0.7334   |
| 1.3058        | 8.0   | 555784 | 1.1777          | 0.7360   |
| 1.2974        | 9.0   | 625257 | 1.1660          | 0.7378   |
| 1.2857        | 10.0  | 694730 | 1.1543          | 0.7401   |
| 1.2755        | 11.0  | 764203 | 1.1514          | 0.7408   |
| 1.2694        | 12.0  | 833676 | 1.1377          | 0.7431   |
| 1.2623        | 13.0  | 903149 | 1.1338          | 0.7442   |
| 1.2587        | 14.0  | 972622 | 1.1279          | 0.7455   |


### Framework versions

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