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# bert-base-chinese-finetuned-ner-food_requirement

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: 0.0046
- 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: 64
- eval_batch_size: 64
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.169         | 1.0   | 3    | 1.7537          | 0.0    |
| 1.598         | 2.0   | 6    | 1.0914          | 0.5169 |
| 1.1569        | 3.0   | 9    | 0.6879          | 0.7057 |
| 0.6669        | 4.0   | 12   | 0.4194          | 0.8607 |
| 0.485         | 5.0   | 15   | 0.2528          | 0.9333 |
| 0.2807        | 6.0   | 18   | 0.1476          | 0.9836 |
| 0.2015        | 7.0   | 21   | 0.0834          | 0.9873 |
| 0.1145        | 8.0   | 24   | 0.0484          | 0.9924 |
| 0.0809        | 9.0   | 27   | 0.0283          | 1.0    |
| 0.0495        | 10.0  | 30   | 0.0180          | 1.0    |
| 0.0377        | 11.0  | 33   | 0.0126          | 1.0    |
| 0.0219        | 12.0  | 36   | 0.0095          | 1.0    |
| 0.0216        | 13.0  | 39   | 0.0076          | 1.0    |
| 0.015         | 14.0  | 42   | 0.0065          | 1.0    |
| 0.0176        | 15.0  | 45   | 0.0059          | 1.0    |
| 0.0161        | 16.0  | 48   | 0.0053          | 1.0    |
| 0.0133        | 17.0  | 51   | 0.0050          | 1.0    |
| 0.0119        | 18.0  | 54   | 0.0048          | 1.0    |
| 0.0116        | 19.0  | 57   | 0.0047          | 1.0    |
| 0.0126        | 20.0  | 60   | 0.0046          | 1.0    |


### Framework versions

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

{"tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "bert-base-chinese-finetuned-ner-food_requirement", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert-base-chinese-finetuned-ner-food\_requirement
=================================================


This model is a fine-tuned version of bert-base-chinese on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0046
* 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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


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



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.12.0+cu102
* Datasets 1.18.4
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.12.0+cu102
* Datasets 1.18.4
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


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