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---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- lener_br
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: lener_br
type: lener_br
config: lener_br
split: validation
args: lener_br
metrics:
- name: Precision
type: precision
value: 0.7640519805855644
- name: Recall
type: recall
value: 0.818242790073776
- name: F1
type: f1
value: 0.7902194154319487
- name: Accuracy
type: accuracy
value: 0.9615441099339138
---
<!-- 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-base-cased-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the lener_br dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.7641
- Recall: 0.8182
- F1: 0.7902
- Accuracy: 0.9615
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 432 | nan | 0.6807 | 0.7773 | 0.7258 | 0.9450 |
| 0.3019 | 2.0 | 864 | nan | 0.7244 | 0.7725 | 0.7476 | 0.9531 |
| 0.0871 | 3.0 | 1296 | nan | 0.7352 | 0.8192 | 0.7749 | 0.9571 |
| 0.0527 | 4.0 | 1728 | nan | 0.7455 | 0.7864 | 0.7654 | 0.9557 |
| 0.031 | 5.0 | 2160 | nan | 0.7334 | 0.7976 | 0.7642 | 0.9544 |
| 0.0223 | 6.0 | 2592 | nan | 0.7703 | 0.8343 | 0.8010 | 0.9624 |
| 0.0171 | 7.0 | 3024 | nan | 0.7279 | 0.8119 | 0.7676 | 0.9569 |
| 0.0171 | 8.0 | 3456 | nan | 0.7609 | 0.8067 | 0.7831 | 0.9613 |
| 0.012 | 9.0 | 3888 | nan | 0.7585 | 0.8152 | 0.7858 | 0.9608 |
| 0.0097 | 10.0 | 4320 | nan | 0.7641 | 0.8182 | 0.7902 | 0.9615 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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