|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- wnut_17 |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: bert-small-finetuned-xglue-ner-longer6 |
|
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: 0.5620094191522763 |
|
- name: Recall |
|
type: recall |
|
value: 0.42822966507177035 |
|
- name: F1 |
|
type: f1 |
|
value: 0.48608282416836385 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9260809725885996 |
|
--- |
|
|
|
<!-- 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-longer6 |
|
|
|
This model is a fine-tuned version of [muhtasham/bert-small-finetuned-xglue-ner](https://huggingface.co/muhtasham/bert-small-finetuned-xglue-ner) on the wnut_17 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4087 |
|
- Precision: 0.5620 |
|
- Recall: 0.4282 |
|
- F1: 0.4861 |
|
- 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: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 425 | 0.3753 | 0.5646 | 0.4127 | 0.4768 | 0.9250 | |
|
| 0.0824 | 2.0 | 850 | 0.3942 | 0.5484 | 0.4270 | 0.4802 | 0.9259 | |
|
| 0.0641 | 3.0 | 1275 | 0.4087 | 0.5620 | 0.4282 | 0.4861 | 0.9261 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
