Downloads · 30 days
7
18% of all-time downloads
bert-finetuned-ner
wgpak/bert-finetuned-ner
bert-finetuned-ner is a token classification model from wgpak. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
40
Public
Parameters
108M
862 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors431 MB · 100%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 29, 2023
- Updated
- Dec 29, 2023
- SHA
- b6e47317
Try a prompt
Base models
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. -->
bert-finetuned-ner
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0590
- Precision: 0.9292
- Recall: 0.9478
- F1: 0.9384
- Accuracy: 0.9854
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0753 | 1.0 | 1756 | 0.0680 | 0.9055 | 0.9317 | 0.9184 | 0.9815 |
| 0.0335 | 2.0 | 3512 | 0.0590 | 0.9292 | 0.9478 | 0.9384 | 0.9854 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 29, 2023
- Updated
- Dec 29, 2023