|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: bert-base-chinese-finetuned-ner-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-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: 0.0039 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 3.0829 | 1.0 | 3 | 1.6749 | 0.0 | |
|
| 1.5535 | 2.0 | 6 | 1.0327 | 0.6354 | |
|
| 1.0573 | 3.0 | 9 | 0.6295 | 0.7097 | |
|
| 0.5854 | 4.0 | 12 | 0.3763 | 0.8271 | |
|
| 0.4292 | 5.0 | 15 | 0.2165 | 0.9059 | |
|
| 0.2235 | 6.0 | 18 | 0.1121 | 0.9836 | |
|
| 0.1535 | 7.0 | 21 | 0.0597 | 0.9975 | |
|
| 0.0846 | 8.0 | 24 | 0.0337 | 0.9975 | |
|
| 0.0613 | 9.0 | 27 | 0.0214 | 1.0 | |
|
| 0.0365 | 10.0 | 30 | 0.0144 | 1.0 | |
|
| 0.0302 | 11.0 | 33 | 0.0103 | 1.0 | |
|
| 0.0182 | 12.0 | 36 | 0.0078 | 1.0 | |
|
| 0.0175 | 13.0 | 39 | 0.0064 | 1.0 | |
|
| 0.0115 | 14.0 | 42 | 0.0055 | 1.0 | |
|
| 0.0124 | 15.0 | 45 | 0.0049 | 1.0 | |
|
| 0.0117 | 16.0 | 48 | 0.0045 | 1.0 | |
|
| 0.0111 | 17.0 | 51 | 0.0042 | 1.0 | |
|
| 0.0102 | 18.0 | 54 | 0.0041 | 1.0 | |
|
| 0.0096 | 19.0 | 57 | 0.0040 | 1.0 | |
|
| 0.0095 | 20.0 | 60 | 0.0039 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.12.0+cu102 |
|
- Datasets 1.18.4 |
|
- Tokenizers 0.12.1 |
|
|
