|
--- |
|
base_model: NlpHUST/ner-vietnamese-electra-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: my_awesome_ner-token_classification_v1.0 |
|
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. --> |
|
|
|
# my_awesome_ner-token_classification_v1.0 |
|
|
|
This model is a fine-tuned version of [NlpHUST/ner-vietnamese-electra-base](https://huggingface.co/NlpHUST/ner-vietnamese-electra-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7184 |
|
- Precision: 0.5603 |
|
- Recall: 0.6333 |
|
- F1: 0.5946 |
|
- Accuracy: 0.8261 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.478 | 1.9991 | 2313 | 0.5109 | 0.5864 | 0.5956 | 0.5910 | 0.8411 | |
|
| 0.3927 | 3.9983 | 4626 | 0.5095 | 0.5834 | 0.6186 | 0.6005 | 0.8401 | |
|
| 0.3111 | 5.9974 | 6939 | 0.5813 | 0.5434 | 0.6335 | 0.5850 | 0.8258 | |
|
| 0.2339 | 7.9965 | 9252 | 0.6137 | 0.5515 | 0.6312 | 0.5887 | 0.8261 | |
|
| 0.1983 | 9.9957 | 11565 | 0.6743 | 0.5719 | 0.6243 | 0.5969 | 0.8305 | |
|
| 0.1565 | 11.9948 | 13878 | 0.7044 | 0.5594 | 0.6372 | 0.5958 | 0.8250 | |
|
| 0.1657 | 13.9939 | 16191 | 0.7184 | 0.5603 | 0.6333 | 0.5946 | 0.8261 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
