Downloads · 30 days
6
2% of all-time downloads
distilbert-base-uncased-finetuned-ner
zboinek/distilbert-base-uncased-finetuned-ner
distilbert-base-uncased-finetuned-ner is a token classification model from zboinek. 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
328
Public
Repo size
2.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin266 MB · 100%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jan 26, 2023
- Updated
- Jan 27, 2023
- SHA
- 396bfc86
Try a prompt
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
This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0639
- Precision: 0.9211
- Recall: 0.9327
- F1: 0.9268
- Accuracy: 0.9824
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 439 | 0.0788 | 0.8907 | 0.9098 | 0.9002 | 0.9785 |
| 0.2157 | 2.0 | 878 | 0.0639 | 0.9130 | 0.9297 | 0.9213 | 0.9813 |
| 0.0586 | 3.0 | 1317 | 0.0639 | 0.9211 | 0.9327 | 0.9268 | 0.9824 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.0a0+d321be6
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 26, 2023
- Updated
- Jan 27, 2023