|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- wnut_17 |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: bert-small-finetuned-xglue-ner-longer20 |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: wnut_17 |
|
type: wnut_17 |
|
config: wnut_17 |
|
split: train |
|
args: wnut_17 |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.5782747603833865 |
|
- name: Recall |
|
type: recall |
|
value: 0.43301435406698563 |
|
- name: F1 |
|
type: f1 |
|
value: 0.4952120383036936 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.92613831861452 |
|
--- |
|
|
|
<!-- 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-small-finetuned-xglue-ner-longer20 |
|
|
|
This model is a fine-tuned version of [muhtasham/bert-small-finetuned-xglue-ner-longer10](https://huggingface.co/muhtasham/bert-small-finetuned-xglue-ner-longer10) on the wnut_17 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5839 |
|
- Precision: 0.5783 |
|
- Recall: 0.4330 |
|
- F1: 0.4952 |
|
- Accuracy: 0.9261 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 425 | 0.4882 | 0.5 | 0.4510 | 0.4742 | 0.9228 | |
|
| 0.013 | 2.0 | 850 | 0.5039 | 0.5130 | 0.4246 | 0.4647 | 0.9242 | |
|
| 0.0124 | 3.0 | 1275 | 0.5331 | 0.5506 | 0.4426 | 0.4907 | 0.9256 | |
|
| 0.0159 | 4.0 | 1700 | 0.5403 | 0.5488 | 0.4234 | 0.4781 | 0.9249 | |
|
| 0.0132 | 5.0 | 2125 | 0.5459 | 0.5714 | 0.4211 | 0.4848 | 0.9255 | |
|
| 0.0117 | 6.0 | 2550 | 0.5522 | 0.5637 | 0.4342 | 0.4905 | 0.9253 | |
|
| 0.0117 | 7.0 | 2975 | 0.5712 | 0.5778 | 0.4354 | 0.4966 | 0.9257 | |
|
| 0.007 | 8.0 | 3400 | 0.5860 | 0.5828 | 0.4378 | 0.5 | 0.9259 | |
|
| 0.0066 | 9.0 | 3825 | 0.5745 | 0.5703 | 0.4462 | 0.5007 | 0.9259 | |
|
| 0.0049 | 10.0 | 4250 | 0.5839 | 0.5783 | 0.4330 | 0.4952 | 0.9261 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
