|
--- |
|
license: apache-2.0 |
|
tags: |
|
- token-classification |
|
datasets: |
|
- wikiann-conll2003 |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
|
|
model-index: |
|
- name: distilroberta-base-ner-wikiann-conll2003-3-class |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: wikiann-conll2003 |
|
type: wikiann-conll2003 |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.9624757386241104 |
|
- name: Recall |
|
type: recall |
|
value: 0.9667497021553124 |
|
- name: F1 |
|
type: f1 |
|
value: 0.964607986167396 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9913626461292995 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# distilroberta-base-ner-wikiann-conll2003-3-class |
|
|
|
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the wikiann-conll2003 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0520 |
|
- Precision: 0.9625 |
|
- Recall: 0.9667 |
|
- F1: 0.9646 |
|
- Accuracy: 0.9914 |
|
|
|
## 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: 4.9086903597787154e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.6.1 |
|
- Pytorch 1.8.1+cu101 |
|
- Datasets 1.6.2 |
|
- Tokenizers 0.10.3 |
|
|
