---
tags:
- generated_from_trainer
metrics:
- f1
base_model: bert-base-chinese
model-index:
- name: bert-base-chinese-finetuned-ner-split_food
  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-base-chinese-finetuned-ner-split_food

This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0077
- F1: 1.0

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6798        | 1.0   | 1    | 1.6743          | 0.0    |
| 1.8172        | 2.0   | 2    | 0.6580          | 0.0    |
| 0.746         | 3.0   | 3    | 0.4864          | 0.0    |
| 0.4899        | 4.0   | 4    | 0.3927          | 0.0    |
| 0.401         | 5.0   | 5    | 0.2753          | 0.0    |
| 0.2963        | 6.0   | 6    | 0.2160          | 0.0    |
| 0.2452        | 7.0   | 7    | 0.1848          | 0.5455 |
| 0.2188        | 8.0   | 8    | 0.1471          | 0.7692 |
| 0.1775        | 9.0   | 9    | 0.1131          | 0.7692 |
| 0.1469        | 10.0  | 10   | 0.0864          | 0.8293 |
| 0.1145        | 11.0  | 11   | 0.0621          | 0.9333 |
| 0.0881        | 12.0  | 12   | 0.0432          | 1.0    |
| 0.0702        | 13.0  | 13   | 0.0329          | 1.0    |
| 0.0531        | 14.0  | 14   | 0.0268          | 1.0    |
| 0.044         | 15.0  | 15   | 0.0184          | 1.0    |
| 0.0321        | 16.0  | 16   | 0.0129          | 1.0    |
| 0.0255        | 17.0  | 17   | 0.0101          | 1.0    |
| 0.0236        | 18.0  | 18   | 0.0087          | 1.0    |
| 0.0254        | 19.0  | 19   | 0.0080          | 1.0    |
| 0.0185        | 20.0  | 20   | 0.0077          | 1.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.12.0+cu102
- Datasets 1.18.4
- Tokenizers 0.12.1