Downloads · 30 days
8
16% of all-time downloads
distilbert-base-multilingual-cased-ner-demo
Amarsanaa1525/distilbert-base-multilingual-cased-ner-demo
distilbert-base-multilingual-cased-ner-demo is a token classification model from Amarsanaa1525. 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
51
Public
Parameters
135M
5.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors539 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 17, 2023
- Updated
- Nov 17, 2023
- SHA
- 8feea41a
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. -->
distilbert-base-multilingual-cased-ner-demo
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1513
- Precision: 0.8756
- Recall: 0.8973
- F1: 0.8863
- Accuracy: 0.9708
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: 32
- 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 |
|---|---|---|---|---|---|---|---|
| 0.2113 | 1.0 | 477 | 0.1338 | 0.7811 | 0.8425 | 0.8107 | 0.9562 |
| 0.1028 | 2.0 | 954 | 0.1159 | 0.8367 | 0.8670 | 0.8515 | 0.9636 |
| 0.0683 | 3.0 | 1431 | 0.1117 | 0.8552 | 0.8824 | 0.8686 | 0.9671 |
| 0.0482 | 4.0 | 1908 | 0.1215 | 0.8608 | 0.8880 | 0.8742 | 0.9682 |
| 0.0331 | 5.0 | 2385 | 0.1243 | 0.8641 | 0.8919 | 0.8778 | 0.9687 |
| 0.0251 | 6.0 | 2862 | 0.1304 | 0.8629 | 0.8901 | 0.8763 | 0.9687 |
| 0.0187 | 7.0 | 3339 | 0.1383 | 0.8695 | 0.8976 | 0.8833 | 0.9702 |
| 0.0126 | 8.0 | 3816 | 0.1489 | 0.8749 | 0.8971 | 0.8859 | 0.9700 |
| 0.0102 | 9.0 | 4293 | 0.1515 | 0.8705 | 0.8961 | 0.8831 | 0.9700 |
| 0.0082 | 10.0 | 4770 | 0.1513 | 0.8756 | 0.8973 | 0.8863 | 0.9708 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- mn
- Created
- Nov 17, 2023
- Updated
- Nov 17, 2023