|
--- |
|
license: cc-by-4.0 |
|
base_model: NazaGara/NER-fine-tuned-BETO |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- conll2002 |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: beto-finetuned-ner |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: conll2002 |
|
type: conll2002 |
|
config: es |
|
split: validation |
|
args: es |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.8347884486232371 |
|
- name: Recall |
|
type: recall |
|
value: 0.8568474264705882 |
|
- name: F1 |
|
type: f1 |
|
value: 0.8456741127111919 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9702609719811555 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# beto-finetuned-ner |
|
|
|
This model is a fine-tuned version of [NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) on the conll2002 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1589 |
|
- Precision: 0.8348 |
|
- Recall: 0.8568 |
|
- F1: 0.8457 |
|
- Accuracy: 0.9703 |
|
|
|
## 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: linear |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.0499 | 1.0 | 521 | 0.1304 | 0.8278 | 0.8536 | 0.8405 | 0.9704 | |
|
| 0.0272 | 2.0 | 1042 | 0.1510 | 0.8355 | 0.8486 | 0.8420 | 0.9687 | |
|
| 0.0153 | 3.0 | 1563 | 0.1589 | 0.8348 | 0.8568 | 0.8457 | 0.9703 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
