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distilbert-base-uncased-finetuned-ner-lenerBr
GuiTap/distilbert-base-uncased-finetuned-ner-lenerBr
distilbert-base-uncased-finetuned-ner-lenerBr is a machine learning model from GuiTap. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Oct 3, 2024
- Updated
- Oct 6, 2024
- SHA
- a7efc1eb
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
distilbert-base-uncased-finetuned-ner-lenerBr
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the lener_br dataset. It achieves the following results on the evaluation set:
- Loss: 0.1555
- Precision: 0.7846
- Recall: 0.7810
- F1: 0.7828
- Accuracy: 0.9672
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 490 | 0.1861 | 0.6380 | 0.6661 | 0.6518 | 0.9446 |
| 0.2629 | 2.0 | 980 | 0.1618 | 0.7063 | 0.7303 | 0.7181 | 0.9537 |
| 0.0756 | 3.0 | 1470 | 0.1299 | 0.7299 | 0.8010 | 0.7638 | 0.9645 |
| 0.0443 | 4.0 | 1960 | 0.1422 | 0.7634 | 0.7708 | 0.7671 | 0.9643 |
| 0.0279 | 5.0 | 2450 | 0.1508 | 0.7870 | 0.7679 | 0.7773 | 0.9648 |
| 0.0203 | 6.0 | 2940 | 0.1457 | 0.7693 | 0.7815 | 0.7753 | 0.9681 |
| 0.0143 | 7.0 | 3430 | 0.1508 | 0.7767 | 0.7714 | 0.7740 | 0.9663 |
| 0.0105 | 8.0 | 3920 | 0.1537 | 0.7812 | 0.7669 | 0.7739 | 0.9671 |
| 0.0085 | 9.0 | 4410 | 0.1564 | 0.7809 | 0.7681 | 0.7745 | 0.9669 |
| 0.0064 | 10.0 | 4900 | 0.1555 | 0.7846 | 0.7810 | 0.7828 | 0.9672 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 3, 2024
- Updated
- Oct 6, 2024