metadata
tags:
- generated_from_trainer
datasets:
- peoples_daily_ner
metrics:
- f1
model-index:
- name: finetuned-bert-chinese-base
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: peoples_daily_ner
type: peoples_daily_ner
config: peoples_daily_ner
split: validation
args: peoples_daily_ner
metrics:
- name: F1
type: f1
value: 0.957080981756136
finetuned-bert-chinese-base
This model is a fine-tuned version of bert-base-chinese on the peoples_daily_ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0185
- F1: 0.9571
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0494 | 1.0 | 1739 | 0.0250 | 0.9283 |
| 0.0146 | 2.0 | 3478 | 0.0202 | 0.9505 |
| 0.0051 | 3.0 | 5217 | 0.0185 | 0.9571 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3