metadata
license: mit
tags:
- generated_from_trainer
datasets:
- harem
metrics:
- precision
- recall
- f1
- accuracy
base_model: neuralmind/bert-base-portuguese-cased
model-index:
- name: bert-base-portuguese-cased_harem-selective-lowC-sm-first-ner
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: harem
type: harem
args: selective
metrics:
- type: precision
value: 0.8
name: Precision
- type: recall
value: 0.8764044943820225
name: Recall
- type: f1
value: 0.8364611260053619
name: F1
- type: accuracy
value: 0.9764089121887287
name: Accuracy
bert-base-portuguese-cased_harem-selective-lowC-sm-first-ner
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the harem dataset. It achieves the following results on the evaluation set:
- Loss: 0.1160
- Precision: 0.8
- Recall: 0.8764
- F1: 0.8365
- Accuracy: 0.9764
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.055 | 1.0 | 2517 | 0.0934 | 0.81 | 0.9101 | 0.8571 | 0.9699 |
| 0.0236 | 2.0 | 5034 | 0.0883 | 0.8307 | 0.8820 | 0.8556 | 0.9751 |
| 0.0129 | 3.0 | 7551 | 0.1160 | 0.8 | 0.8764 | 0.8365 | 0.9764 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1