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-sm-first-ner
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: harem
type: harem
args: selective
metrics:
- type: precision
value: 0.7455830388692579
name: Precision
- type: recall
value: 0.8053435114503816
name: Recall
- type: f1
value: 0.7743119266055045
name: F1
- type: accuracy
value: 0.964875491480996
name: Accuracy
bert-base-portuguese-cased_harem-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: 0.1952
- Precision: 0.7456
- Recall: 0.8053
- F1: 0.7743
- Accuracy: 0.9649
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 |
|---|---|---|---|---|---|---|---|
| 0.1049 | 1.0 | 2517 | 0.1955 | 0.6601 | 0.7710 | 0.7113 | 0.9499 |
| 0.0622 | 2.0 | 5034 | 0.2097 | 0.7314 | 0.7901 | 0.7596 | 0.9554 |
| 0.0318 | 3.0 | 7551 | 0.1952 | 0.7456 | 0.8053 | 0.7743 | 0.9649 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1